diff --git a/core/src/main/scala/org/apache/spark/SparkEnv.scala b/core/src/main/scala/org/apache/spark/SparkEnv.scala index dd95e406f2a8e..009ed64775844 100644 --- a/core/src/main/scala/org/apache/spark/SparkEnv.scala +++ b/core/src/main/scala/org/apache/spark/SparkEnv.scala @@ -108,6 +108,14 @@ class SparkEnv ( pythonWorkers.get(key).foreach(_.stopWorker(worker)) } } + + private[spark] + def releasePythonWorker(pythonExec: String, envVars: Map[String, String], worker: Socket) { + synchronized { + val key = (pythonExec, envVars) + pythonWorkers.get(key).foreach(_.releaseWorker(worker)) + } + } } object SparkEnv extends Logging { diff --git a/core/src/main/scala/org/apache/spark/api/python/PythonRDD.scala b/core/src/main/scala/org/apache/spark/api/python/PythonRDD.scala index ae8010300a500..d5002fa02992b 100644 --- a/core/src/main/scala/org/apache/spark/api/python/PythonRDD.scala +++ b/core/src/main/scala/org/apache/spark/api/python/PythonRDD.scala @@ -23,6 +23,7 @@ import java.nio.charset.Charset import java.util.{List => JList, ArrayList => JArrayList, Map => JMap, Collections} import scala.collection.JavaConversions._ +import scala.collection.mutable import scala.language.existentials import scala.reflect.ClassTag import scala.util.{Try, Success, Failure} @@ -52,6 +53,7 @@ private[spark] class PythonRDD( extends RDD[Array[Byte]](parent) { val bufferSize = conf.getInt("spark.buffer.size", 65536) + val reuse_worker = conf.getBoolean("spark.python.worker.reuse", true) override def getPartitions = parent.partitions @@ -63,19 +65,26 @@ private[spark] class PythonRDD( val localdir = env.blockManager.diskBlockManager.localDirs.map( f => f.getPath()).mkString(",") envVars += ("SPARK_LOCAL_DIRS" -> localdir) // it's also used in monitor thread + if (reuse_worker) { + envVars += ("SPARK_REUSE_WORKER" -> "1") + } val worker: Socket = env.createPythonWorker(pythonExec, envVars.toMap) // Start a thread to feed the process input from our parent's iterator val writerThread = new WriterThread(env, worker, split, context) + var complete_cleanly = false context.addTaskCompletionListener { context => writerThread.shutdownOnTaskCompletion() - - // Cleanup the worker socket. This will also cause the Python worker to exit. - try { - worker.close() - } catch { - case e: Exception => logWarning("Failed to close worker socket", e) + if (reuse_worker && complete_cleanly) { + env.releasePythonWorker(pythonExec, envVars.toMap, worker) + } else { + try { + worker.close() + } catch { + case e: Exception => + logWarning("Failed to close worker socket", e) + } } } @@ -115,6 +124,10 @@ private[spark] class PythonRDD( val total = finishTime - startTime logInfo("Times: total = %s, boot = %s, init = %s, finish = %s".format(total, boot, init, finish)) + val memoryBytesSpilled = stream.readLong() + val diskBytesSpilled = stream.readLong() + context.taskMetrics.memoryBytesSpilled += memoryBytesSpilled + context.taskMetrics.diskBytesSpilled += diskBytesSpilled read() case SpecialLengths.PYTHON_EXCEPTION_THROWN => // Signals that an exception has been thrown in python @@ -133,6 +146,7 @@ private[spark] class PythonRDD( stream.readFully(update) accumulator += Collections.singletonList(update) } + complete_cleanly = true null } } catch { @@ -195,11 +209,26 @@ private[spark] class PythonRDD( PythonRDD.writeUTF(include, dataOut) } // Broadcast variables - dataOut.writeInt(broadcastVars.length) + val oldBids = PythonRDD.getWorkerBroadcasts(worker) + val newBids = broadcastVars.map(_.id).toSet + // number of different broadcasts + val cnt = oldBids.diff(newBids).size + newBids.diff(oldBids).size + dataOut.writeInt(cnt) + for (bid <- oldBids) { + if (!newBids.contains(bid)) { + // remove the broadcast from worker + dataOut.writeLong(- bid - 1) // bid >= 0 + oldBids.remove(bid) + } + } for (broadcast <- broadcastVars) { - dataOut.writeLong(broadcast.id) - dataOut.writeInt(broadcast.value.length) - dataOut.write(broadcast.value) + if (!oldBids.contains(broadcast.id)) { + // send new broadcast + dataOut.writeLong(broadcast.id) + dataOut.writeInt(broadcast.value.length) + dataOut.write(broadcast.value) + oldBids.add(broadcast.id) + } } dataOut.flush() // Serialized command: @@ -207,17 +236,18 @@ private[spark] class PythonRDD( dataOut.write(command) // Data values PythonRDD.writeIteratorToStream(parent.iterator(split, context), dataOut) + dataOut.writeInt(SpecialLengths.END_OF_DATA_SECTION) dataOut.flush() } catch { case e: Exception if context.isCompleted || context.isInterrupted => logDebug("Exception thrown after task completion (likely due to cleanup)", e) + worker.shutdownOutput() case e: Exception => // We must avoid throwing exceptions here, because the thread uncaught exception handler // will kill the whole executor (see org.apache.spark.executor.Executor). _exception = e - } finally { - Try(worker.shutdownOutput()) // kill Python worker process + worker.shutdownOutput() } } } @@ -278,6 +308,14 @@ private object SpecialLengths { private[spark] object PythonRDD extends Logging { val UTF8 = Charset.forName("UTF-8") + // remember the broadcasts sent to each worker + private val workerBroadcasts = new mutable.WeakHashMap[Socket, mutable.Set[Long]]() + private def getWorkerBroadcasts(worker: Socket) = { + synchronized { + workerBroadcasts.getOrElseUpdate(worker, new mutable.HashSet[Long]()) + } + } + /** * Adapter for calling SparkContext#runJob from Python. * diff --git a/core/src/main/scala/org/apache/spark/api/python/PythonWorkerFactory.scala b/core/src/main/scala/org/apache/spark/api/python/PythonWorkerFactory.scala index 4c4796f6c59ba..71bdf0fe1b917 100644 --- a/core/src/main/scala/org/apache/spark/api/python/PythonWorkerFactory.scala +++ b/core/src/main/scala/org/apache/spark/api/python/PythonWorkerFactory.scala @@ -40,7 +40,10 @@ private[spark] class PythonWorkerFactory(pythonExec: String, envVars: Map[String var daemon: Process = null val daemonHost = InetAddress.getByAddress(Array(127, 0, 0, 1)) var daemonPort: Int = 0 - var daemonWorkers = new mutable.WeakHashMap[Socket, Int]() + val daemonWorkers = new mutable.WeakHashMap[Socket, Int]() + val idleWorkers = new mutable.Queue[Socket]() + var lastActivity = 0L + new MonitorThread().start() var simpleWorkers = new mutable.WeakHashMap[Socket, Process]() @@ -51,6 +54,11 @@ private[spark] class PythonWorkerFactory(pythonExec: String, envVars: Map[String def create(): Socket = { if (useDaemon) { + synchronized { + if (idleWorkers.size > 0) { + return idleWorkers.dequeue() + } + } createThroughDaemon() } else { createSimpleWorker() @@ -199,9 +207,44 @@ private[spark] class PythonWorkerFactory(pythonExec: String, envVars: Map[String } } + /** + * Monitor all the idle workers, kill them after timeout. + */ + private class MonitorThread extends Thread(s"Idle Worker Monitor for $pythonExec") { + + setDaemon(true) + + override def run() { + while (true) { + synchronized { + if (lastActivity + IDLE_WORKER_TIMEOUT_MS < System.currentTimeMillis()) { + cleanupIdleWorkers() + lastActivity = System.currentTimeMillis() + } + } + Thread.sleep(10000) + } + } + } + + private def cleanupIdleWorkers() { + while (idleWorkers.length > 0) { + val worker = idleWorkers.dequeue() + try { + // the worker will exit after closing the socket + worker.close() + } catch { + case e: Exception => + logWarning("Failed to close worker socket", e) + } + } + } + private def stopDaemon() { synchronized { if (useDaemon) { + cleanupIdleWorkers() + // Request shutdown of existing daemon by sending SIGTERM if (daemon != null) { daemon.destroy() @@ -220,23 +263,43 @@ private[spark] class PythonWorkerFactory(pythonExec: String, envVars: Map[String } def stopWorker(worker: Socket) { - if (useDaemon) { - if (daemon != null) { - daemonWorkers.get(worker).foreach { pid => - // tell daemon to kill worker by pid - val output = new DataOutputStream(daemon.getOutputStream) - output.writeInt(pid) - output.flush() - daemon.getOutputStream.flush() + synchronized { + if (useDaemon) { + if (daemon != null) { + daemonWorkers.get(worker).foreach { pid => + // tell daemon to kill worker by pid + val output = new DataOutputStream(daemon.getOutputStream) + output.writeInt(pid) + output.flush() + daemon.getOutputStream.flush() + } } + } else { + simpleWorkers.get(worker).foreach(_.destroy()) } - } else { - simpleWorkers.get(worker).foreach(_.destroy()) } worker.close() } + + def releaseWorker(worker: Socket) { + if (useDaemon) { + synchronized { + lastActivity = System.currentTimeMillis() + idleWorkers.enqueue(worker) + } + } else { + // Cleanup the worker socket. This will also cause the Python worker to exit. + try { + worker.close() + } catch { + case e: Exception => + logWarning("Failed to close worker socket", e) + } + } + } } private object PythonWorkerFactory { val PROCESS_WAIT_TIMEOUT_MS = 10000 + val IDLE_WORKER_TIMEOUT_MS = 60000 // kill idle workers after 1 minute } diff --git a/docs/configuration.md b/docs/configuration.md index 36178efb97103..af16489a44281 100644 --- a/docs/configuration.md +++ b/docs/configuration.md @@ -206,6 +206,16 @@ Apart from these, the following properties are also available, and may be useful used during aggregation goes above this amount, it will spill the data into disks. + + spark.python.worker.reuse + true + + Reuse Python worker or not. If yes, it will use a fixed number of Python workers, + does not need to fork() a Python process for every tasks. It will be very useful + if there is large broadcast, then the broadcast will not be needed to transfered + from JVM to Python worker for every task. + + spark.executorEnv.[EnvironmentVariableName] (none) diff --git a/docs/sql-programming-guide.md b/docs/sql-programming-guide.md index 3159d52787d5a..8d41fdec699e9 100644 --- a/docs/sql-programming-guide.md +++ b/docs/sql-programming-guide.md @@ -918,7 +918,6 @@ options. ## Migration Guide for Shark User ### Scheduling -s To set a [Fair Scheduler](job-scheduling.html#fair-scheduler-pools) pool for a JDBC client session, users can set the `spark.sql.thriftserver.scheduler.pool` variable: @@ -1110,7 +1109,7 @@ evaluated by the SQL execution engine. A full list of the functions supported c The range of numbers is from `-9223372036854775808` to `9223372036854775807`. - `FloatType`: Represents 4-byte single-precision floating point numbers. - `DoubleType`: Represents 8-byte double-precision floating point numbers. - - `DecimalType`: + - `DecimalType`: Represents arbitrary-precision signed decimal numbers. Backed internally by `java.math.BigDecimal`. A `BigDecimal` consists of an arbitrary precision integer unscaled value and a 32-bit integer scale. * String type - `StringType`: Represents character string values. * Binary type diff --git a/python/pyspark/daemon.py b/python/pyspark/daemon.py index 15445abf67147..64d6202acb27d 100644 --- a/python/pyspark/daemon.py +++ b/python/pyspark/daemon.py @@ -23,6 +23,7 @@ import sys import traceback import time +import gc from errno import EINTR, ECHILD, EAGAIN from socket import AF_INET, SOCK_STREAM, SOMAXCONN from signal import SIGHUP, SIGTERM, SIGCHLD, SIG_DFL, SIG_IGN @@ -46,17 +47,6 @@ def worker(sock): signal.signal(SIGCHLD, SIG_DFL) signal.signal(SIGTERM, SIG_DFL) - # Blocks until the socket is closed by draining the input stream - # until it raises an exception or returns EOF. - def waitSocketClose(sock): - try: - while True: - # Empty string is returned upon EOF (and only then). - if sock.recv(4096) == '': - return - except: - pass - # Read the socket using fdopen instead of socket.makefile() because the latter # seems to be very slow; note that we need to dup() the file descriptor because # otherwise writes also cause a seek that makes us miss data on the read side. @@ -64,17 +54,13 @@ def waitSocketClose(sock): outfile = os.fdopen(os.dup(sock.fileno()), "a+", 65536) exit_code = 0 try: - # Acknowledge that the fork was successful - write_int(os.getpid(), outfile) - outfile.flush() worker_main(infile, outfile) except SystemExit as exc: - exit_code = exc.code + exit_code = compute_real_exit_code(exc.code) finally: outfile.flush() - # The Scala side will close the socket upon task completion. - waitSocketClose(sock) - os._exit(compute_real_exit_code(exit_code)) + if exit_code: + os._exit(exit_code) # Cleanup zombie children @@ -111,6 +97,8 @@ def handle_sigterm(*args): signal.signal(SIGTERM, handle_sigterm) # Gracefully exit on SIGTERM signal.signal(SIGHUP, SIG_IGN) # Don't die on SIGHUP + reuse = os.environ.get("SPARK_REUSE_WORKER") + # Initialization complete try: while True: @@ -163,7 +151,19 @@ def handle_sigterm(*args): # in child process listen_sock.close() try: - worker(sock) + # Acknowledge that the fork was successful + outfile = sock.makefile("w") + write_int(os.getpid(), outfile) + outfile.flush() + outfile.close() + while True: + worker(sock) + if not reuse: + # wait for closing + while sock.recv(1024): + pass + break + gc.collect() except: traceback.print_exc() os._exit(1) diff --git a/python/pyspark/mllib/_common.py b/python/pyspark/mllib/_common.py index bb60d3d0c8463..68f6033616726 100644 --- a/python/pyspark/mllib/_common.py +++ b/python/pyspark/mllib/_common.py @@ -21,7 +21,7 @@ from numpy import ndarray, float64, int64, int32, array_equal, array from pyspark import SparkContext, RDD from pyspark.mllib.linalg import SparseVector -from pyspark.serializers import Serializer +from pyspark.serializers import FramedSerializer """ @@ -451,18 +451,16 @@ def _serialize_rating(r): return ba -class RatingDeserializer(Serializer): +class RatingDeserializer(FramedSerializer): - def loads(self, stream): - length = struct.unpack("!i", stream.read(4))[0] - ba = stream.read(length) - res = ndarray(shape=(3, ), buffer=ba, dtype=float64, offset=4) + def loads(self, string): + res = ndarray(shape=(3, ), buffer=string, dtype=float64, offset=4) return int(res[0]), int(res[1]), res[2] def load_stream(self, stream): while True: try: - yield self.loads(stream) + yield self._read_with_length(stream) except struct.error: return except EOFError: diff --git a/python/pyspark/serializers.py b/python/pyspark/serializers.py index a5f9341e819a9..ec3c6f055441d 100644 --- a/python/pyspark/serializers.py +++ b/python/pyspark/serializers.py @@ -144,6 +144,8 @@ def _write_with_length(self, obj, stream): def _read_with_length(self, stream): length = read_int(stream) + if length == SpecialLengths.END_OF_DATA_SECTION: + raise EOFError obj = stream.read(length) if obj == "": raise EOFError @@ -438,6 +440,8 @@ def __init__(self, use_unicode=False): def loads(self, stream): length = read_int(stream) + if length == SpecialLengths.END_OF_DATA_SECTION: + raise EOFError s = stream.read(length) return s.decode("utf-8") if self.use_unicode else s diff --git a/python/pyspark/shuffle.py b/python/pyspark/shuffle.py index 49829f5280a5f..ce597cbe91e15 100644 --- a/python/pyspark/shuffle.py +++ b/python/pyspark/shuffle.py @@ -68,6 +68,11 @@ def _get_local_dirs(sub): return [os.path.join(d, "python", str(os.getpid()), sub) for d in dirs] +# global stats +MemoryBytesSpilled = 0L +DiskBytesSpilled = 0L + + class Aggregator(object): """ @@ -313,10 +318,12 @@ def _spill(self): It will dump the data in batch for better performance. """ + global MemoryBytesSpilled, DiskBytesSpilled path = self._get_spill_dir(self.spills) if not os.path.exists(path): os.makedirs(path) + used_memory = get_used_memory() if not self.pdata: # The data has not been partitioned, it will iterator the # dataset once, write them into different files, has no @@ -334,6 +341,7 @@ def _spill(self): self.serializer.dump_stream([(k, v)], streams[h]) for s in streams: + DiskBytesSpilled += s.tell() s.close() self.data.clear() @@ -346,9 +354,11 @@ def _spill(self): # dump items in batch self.serializer.dump_stream(self.pdata[i].iteritems(), f) self.pdata[i].clear() + DiskBytesSpilled += os.path.getsize(p) self.spills += 1 gc.collect() # release the memory as much as possible + MemoryBytesSpilled += (used_memory - get_used_memory()) << 20 def iteritems(self): """ Return all merged items as iterator """ @@ -462,7 +472,6 @@ def __init__(self, memory_limit, serializer=None): self.memory_limit = memory_limit self.local_dirs = _get_local_dirs("sort") self.serializer = serializer or BatchedSerializer(PickleSerializer(), 1024) - self._spilled_bytes = 0 def _get_path(self, n): """ Choose one directory for spill by number n """ @@ -476,6 +485,7 @@ def sorted(self, iterator, key=None, reverse=False): Sort the elements in iterator, do external sort when the memory goes above the limit. """ + global MemoryBytesSpilled, DiskBytesSpilled batch = 10 chunks, current_chunk = [], [] iterator = iter(iterator) @@ -486,15 +496,18 @@ def sorted(self, iterator, key=None, reverse=False): if len(chunk) < batch: break - if get_used_memory() > self.memory_limit: + used_memory = get_used_memory() + if used_memory > self.memory_limit: # sort them inplace will save memory current_chunk.sort(key=key, reverse=reverse) path = self._get_path(len(chunks)) with open(path, 'w') as f: self.serializer.dump_stream(current_chunk, f) - self._spilled_bytes += os.path.getsize(path) chunks.append(self.serializer.load_stream(open(path))) current_chunk = [] + gc.collect() + MemoryBytesSpilled += (used_memory - get_used_memory()) << 20 + DiskBytesSpilled += os.path.getsize(path) elif not chunks: batch = min(batch * 2, 10000) diff --git a/python/pyspark/tests.py b/python/pyspark/tests.py index b687d695b01c4..f3309a20fcffb 100644 --- a/python/pyspark/tests.py +++ b/python/pyspark/tests.py @@ -46,6 +46,7 @@ CloudPickleSerializer from pyspark.shuffle import Aggregator, InMemoryMerger, ExternalMerger, ExternalSorter from pyspark.sql import SQLContext, IntegerType +from pyspark import shuffle _have_scipy = False _have_numpy = False @@ -138,17 +139,17 @@ def test_external_sort(self): random.shuffle(l) sorter = ExternalSorter(1) self.assertEquals(sorted(l), list(sorter.sorted(l))) - self.assertGreater(sorter._spilled_bytes, 0) - last = sorter._spilled_bytes + self.assertGreater(shuffle.DiskBytesSpilled, 0) + last = shuffle.DiskBytesSpilled self.assertEquals(sorted(l, reverse=True), list(sorter.sorted(l, reverse=True))) - self.assertGreater(sorter._spilled_bytes, last) - last = sorter._spilled_bytes + self.assertGreater(shuffle.DiskBytesSpilled, last) + last = shuffle.DiskBytesSpilled self.assertEquals(sorted(l, key=lambda x: -x), list(sorter.sorted(l, key=lambda x: -x))) - self.assertGreater(sorter._spilled_bytes, last) - last = sorter._spilled_bytes + self.assertGreater(shuffle.DiskBytesSpilled, last) + last = shuffle.DiskBytesSpilled self.assertEquals(sorted(l, key=lambda x: -x, reverse=True), list(sorter.sorted(l, key=lambda x: -x, reverse=True))) - self.assertGreater(sorter._spilled_bytes, last) + self.assertGreater(shuffle.DiskBytesSpilled, last) def test_external_sort_in_rdd(self): conf = SparkConf().set("spark.python.worker.memory", "1m") @@ -1222,11 +1223,46 @@ def run(): except OSError: self.fail("daemon had been killed") + # run a normal job + rdd = self.sc.parallelize(range(100), 1) + self.assertEqual(100, rdd.map(str).count()) + def test_fd_leak(self): N = 1100 # fd limit is 1024 by default rdd = self.sc.parallelize(range(N), N) self.assertEquals(N, rdd.count()) + def test_after_exception(self): + def raise_exception(_): + raise Exception() + rdd = self.sc.parallelize(range(100), 1) + self.assertRaises(Exception, lambda: rdd.foreach(raise_exception)) + self.assertEqual(100, rdd.map(str).count()) + + def test_after_jvm_exception(self): + tempFile = tempfile.NamedTemporaryFile(delete=False) + tempFile.write("Hello World!") + tempFile.close() + data = self.sc.textFile(tempFile.name, 1) + filtered_data = data.filter(lambda x: True) + self.assertEqual(1, filtered_data.count()) + os.unlink(tempFile.name) + self.assertRaises(Exception, lambda: filtered_data.count()) + + rdd = self.sc.parallelize(range(100), 1) + self.assertEqual(100, rdd.map(str).count()) + + def test_accumulator_when_reuse_worker(self): + from pyspark.accumulators import INT_ACCUMULATOR_PARAM + acc1 = self.sc.accumulator(0, INT_ACCUMULATOR_PARAM) + self.sc.parallelize(range(100), 20).foreach(lambda x: acc1.add(x)) + self.assertEqual(sum(range(100)), acc1.value) + + acc2 = self.sc.accumulator(0, INT_ACCUMULATOR_PARAM) + self.sc.parallelize(range(100), 20).foreach(lambda x: acc2.add(x)) + self.assertEqual(sum(range(100)), acc2.value) + self.assertEqual(sum(range(100)), acc1.value) + class TestSparkSubmit(unittest.TestCase): diff --git a/python/pyspark/worker.py b/python/pyspark/worker.py index 6805063e06798..252176ac65fec 100644 --- a/python/pyspark/worker.py +++ b/python/pyspark/worker.py @@ -23,16 +23,14 @@ import time import socket import traceback -# CloudPickler needs to be imported so that depicklers are registered using the -# copy_reg module. + from pyspark.accumulators import _accumulatorRegistry from pyspark.broadcast import Broadcast, _broadcastRegistry -from pyspark.cloudpickle import CloudPickler from pyspark.files import SparkFiles from pyspark.serializers import write_with_length, write_int, read_long, \ write_long, read_int, SpecialLengths, UTF8Deserializer, PickleSerializer, \ CompressedSerializer - +from pyspark import shuffle pickleSer = PickleSerializer() utf8_deserializer = UTF8Deserializer() @@ -52,6 +50,11 @@ def main(infile, outfile): if split_index == -1: # for unit tests return + # initialize global state + shuffle.MemoryBytesSpilled = 0 + shuffle.DiskBytesSpilled = 0 + _accumulatorRegistry.clear() + # fetch name of workdir spark_files_dir = utf8_deserializer.loads(infile) SparkFiles._root_directory = spark_files_dir @@ -69,9 +72,14 @@ def main(infile, outfile): ser = CompressedSerializer(pickleSer) for _ in range(num_broadcast_variables): bid = read_long(infile) - value = ser._read_with_length(infile) - _broadcastRegistry[bid] = Broadcast(bid, value) + if bid >= 0: + value = ser._read_with_length(infile) + _broadcastRegistry[bid] = Broadcast(bid, value) + else: + bid = - bid - 1 + _broadcastRegistry.remove(bid) + _accumulatorRegistry.clear() command = pickleSer._read_with_length(infile) (func, deserializer, serializer) = command init_time = time.time() @@ -92,6 +100,9 @@ def main(infile, outfile): exit(-1) finish_time = time.time() report_times(outfile, boot_time, init_time, finish_time) + write_long(shuffle.MemoryBytesSpilled, outfile) + write_long(shuffle.DiskBytesSpilled, outfile) + # Mark the beginning of the accumulators section of the output write_int(SpecialLengths.END_OF_DATA_SECTION, outfile) write_int(len(_accumulatorRegistry), outfile) diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SqlParser.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SqlParser.scala index ca69531c69a77..068cb49ef6d34 100755 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SqlParser.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SqlParser.scala @@ -151,7 +151,7 @@ class SqlParser extends StandardTokenParsers with PackratParsers { EXCEPT ^^^ { (q1: LogicalPlan, q2: LogicalPlan) => Except(q1, q2)} | UNION ~ opt(DISTINCT) ^^^ { (q1: LogicalPlan, q2: LogicalPlan) => Distinct(Union(q1, q2)) } ) - | insert | cache + | insert | cache | unCache ) protected lazy val select: Parser[LogicalPlan] = @@ -183,9 +183,17 @@ class SqlParser extends StandardTokenParsers with PackratParsers { } protected lazy val cache: Parser[LogicalPlan] = - (CACHE ^^^ true | UNCACHE ^^^ false) ~ TABLE ~ ident ^^ { - case doCache ~ _ ~ tableName => CacheCommand(tableName, doCache) + CACHE ~ TABLE ~> ident ~ opt(AS ~ select) <~ opt(";") ^^ { + case tableName ~ None => + CacheCommand(tableName, true) + case tableName ~ Some(as ~ plan) => + CacheTableAsSelectCommand(tableName, plan) } + + protected lazy val unCache: Parser[LogicalPlan] = + UNCACHE ~ TABLE ~> ident <~ opt(";") ^^ { + case tableName => CacheCommand(tableName, false) + } protected lazy val projections: Parser[Seq[Expression]] = repsep(projection, ",") diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/SpecificRow.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/SpecificRow.scala index 088f11ee4aa53..9cbab3d5d0d0d 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/SpecificRow.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/SpecificRow.scala @@ -171,7 +171,7 @@ final class MutableByte extends MutableValue { } final class MutableAny extends MutableValue { - var value: Any = 0 + var value: Any = _ def boxed = if (isNull) null else value def update(v: Any) = value = { isNull = false diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/commands.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/commands.scala index a01809c1fc5e2..8366639fa0e8b 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/commands.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/commands.scala @@ -75,3 +75,8 @@ case class DescribeCommand( AttributeReference("data_type", StringType, nullable = false)(), AttributeReference("comment", StringType, nullable = false)()) } + +/** + * Returned for the "CACHE TABLE tableName AS SELECT .." command. + */ +case class CacheTableAsSelectCommand(tableName: String, plan: LogicalPlan) extends Command diff --git a/sql/core/src/main/scala/org/apache/spark/sql/columnar/ColumnAccessor.scala b/sql/core/src/main/scala/org/apache/spark/sql/columnar/ColumnAccessor.scala index 42a5a9a84f362..c9faf0852142a 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/columnar/ColumnAccessor.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/columnar/ColumnAccessor.scala @@ -50,11 +50,13 @@ private[sql] abstract class BasicColumnAccessor[T <: DataType, JvmType]( def hasNext = buffer.hasRemaining - def extractTo(row: MutableRow, ordinal: Int) { - columnType.setField(row, ordinal, extractSingle(buffer)) + def extractTo(row: MutableRow, ordinal: Int): Unit = { + extractSingle(row, ordinal) } - def extractSingle(buffer: ByteBuffer): JvmType = columnType.extract(buffer) + def extractSingle(row: MutableRow, ordinal: Int): Unit = { + columnType.extract(buffer, row, ordinal) + } protected def underlyingBuffer = buffer } diff --git a/sql/core/src/main/scala/org/apache/spark/sql/columnar/ColumnBuilder.scala b/sql/core/src/main/scala/org/apache/spark/sql/columnar/ColumnBuilder.scala index b3ec5ded22422..2e61a981375aa 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/columnar/ColumnBuilder.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/columnar/ColumnBuilder.scala @@ -68,10 +68,9 @@ private[sql] class BasicColumnBuilder[T <: DataType, JvmType]( buffer.order(ByteOrder.nativeOrder()).putInt(columnType.typeId) } - override def appendFrom(row: Row, ordinal: Int) { - val field = columnType.getField(row, ordinal) - buffer = ensureFreeSpace(buffer, columnType.actualSize(field)) - columnType.append(field, buffer) + override def appendFrom(row: Row, ordinal: Int): Unit = { + buffer = ensureFreeSpace(buffer, columnType.actualSize(row, ordinal)) + columnType.append(row, ordinal, buffer) } override def build() = { @@ -142,16 +141,16 @@ private[sql] object ColumnBuilder { useCompression: Boolean = false): ColumnBuilder = { val builder = (typeId match { - case INT.typeId => new IntColumnBuilder - case LONG.typeId => new LongColumnBuilder - case FLOAT.typeId => new FloatColumnBuilder - case DOUBLE.typeId => new DoubleColumnBuilder - case BOOLEAN.typeId => new BooleanColumnBuilder - case BYTE.typeId => new ByteColumnBuilder - case SHORT.typeId => new ShortColumnBuilder - case STRING.typeId => new StringColumnBuilder - case BINARY.typeId => new BinaryColumnBuilder - case GENERIC.typeId => new GenericColumnBuilder + case INT.typeId => new IntColumnBuilder + case LONG.typeId => new LongColumnBuilder + case FLOAT.typeId => new FloatColumnBuilder + case DOUBLE.typeId => new DoubleColumnBuilder + case BOOLEAN.typeId => new BooleanColumnBuilder + case BYTE.typeId => new ByteColumnBuilder + case SHORT.typeId => new ShortColumnBuilder + case STRING.typeId => new StringColumnBuilder + case BINARY.typeId => new BinaryColumnBuilder + case GENERIC.typeId => new GenericColumnBuilder case TIMESTAMP.typeId => new TimestampColumnBuilder }).asInstanceOf[ColumnBuilder] diff --git a/sql/core/src/main/scala/org/apache/spark/sql/columnar/ColumnStats.scala b/sql/core/src/main/scala/org/apache/spark/sql/columnar/ColumnStats.scala index fc343ccb995c2..203a714e03c97 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/columnar/ColumnStats.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/columnar/ColumnStats.scala @@ -69,7 +69,7 @@ private[sql] class ByteColumnStats extends ColumnStats { var lower = Byte.MaxValue var nullCount = 0 - override def gatherStats(row: Row, ordinal: Int) { + override def gatherStats(row: Row, ordinal: Int): Unit = { if (!row.isNullAt(ordinal)) { val value = row.getByte(ordinal) if (value > upper) upper = value @@ -87,7 +87,7 @@ private[sql] class ShortColumnStats extends ColumnStats { var lower = Short.MaxValue var nullCount = 0 - override def gatherStats(row: Row, ordinal: Int) { + override def gatherStats(row: Row, ordinal: Int): Unit = { if (!row.isNullAt(ordinal)) { val value = row.getShort(ordinal) if (value > upper) upper = value @@ -105,7 +105,7 @@ private[sql] class LongColumnStats extends ColumnStats { var lower = Long.MaxValue var nullCount = 0 - override def gatherStats(row: Row, ordinal: Int) { + override def gatherStats(row: Row, ordinal: Int): Unit = { if (!row.isNullAt(ordinal)) { val value = row.getLong(ordinal) if (value > upper) upper = value @@ -123,7 +123,7 @@ private[sql] class DoubleColumnStats extends ColumnStats { var lower = Double.MaxValue var nullCount = 0 - override def gatherStats(row: Row, ordinal: Int) { + override def gatherStats(row: Row, ordinal: Int): Unit = { if (!row.isNullAt(ordinal)) { val value = row.getDouble(ordinal) if (value > upper) upper = value @@ -141,7 +141,7 @@ private[sql] class FloatColumnStats extends ColumnStats { var lower = Float.MaxValue var nullCount = 0 - override def gatherStats(row: Row, ordinal: Int) { + override def gatherStats(row: Row, ordinal: Int): Unit = { if (!row.isNullAt(ordinal)) { val value = row.getFloat(ordinal) if (value > upper) upper = value @@ -159,7 +159,7 @@ private[sql] class IntColumnStats extends ColumnStats { var lower = Int.MaxValue var nullCount = 0 - override def gatherStats(row: Row, ordinal: Int) { + override def gatherStats(row: Row, ordinal: Int): Unit = { if (!row.isNullAt(ordinal)) { val value = row.getInt(ordinal) if (value > upper) upper = value @@ -177,7 +177,7 @@ private[sql] class StringColumnStats extends ColumnStats { var lower: String = null var nullCount = 0 - override def gatherStats(row: Row, ordinal: Int) { + override def gatherStats(row: Row, ordinal: Int): Unit = { if (!row.isNullAt(ordinal)) { val value = row.getString(ordinal) if (upper == null || value.compareTo(upper) > 0) upper = value @@ -195,7 +195,7 @@ private[sql] class TimestampColumnStats extends ColumnStats { var lower: Timestamp = null var nullCount = 0 - override def gatherStats(row: Row, ordinal: Int) { + override def gatherStats(row: Row, ordinal: Int): Unit = { if (!row.isNullAt(ordinal)) { val value = row(ordinal).asInstanceOf[Timestamp] if (upper == null || value.compareTo(upper) > 0) upper = value diff --git a/sql/core/src/main/scala/org/apache/spark/sql/columnar/ColumnType.scala b/sql/core/src/main/scala/org/apache/spark/sql/columnar/ColumnType.scala index 9a61600115872..198b5756676aa 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/columnar/ColumnType.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/columnar/ColumnType.scala @@ -18,11 +18,10 @@ package org.apache.spark.sql.columnar import java.nio.ByteBuffer +import java.sql.Timestamp import scala.reflect.runtime.universe.TypeTag -import java.sql.Timestamp - import org.apache.spark.sql.Row import org.apache.spark.sql.catalyst.expressions.MutableRow import org.apache.spark.sql.catalyst.types._ @@ -46,16 +45,33 @@ private[sql] sealed abstract class ColumnType[T <: DataType, JvmType]( */ def extract(buffer: ByteBuffer): JvmType + /** + * Extracts a value out of the buffer at the buffer's current position and stores in + * `row(ordinal)`. Subclasses should override this method to avoid boxing/unboxing costs whenever + * possible. + */ + def extract(buffer: ByteBuffer, row: MutableRow, ordinal: Int): Unit = { + setField(row, ordinal, extract(buffer)) + } + /** * Appends the given value v of type T into the given ByteBuffer. */ - def append(v: JvmType, buffer: ByteBuffer) + def append(v: JvmType, buffer: ByteBuffer): Unit + + /** + * Appends `row(ordinal)` of type T into the given ByteBuffer. Subclasses should override this + * method to avoid boxing/unboxing costs whenever possible. + */ + def append(row: Row, ordinal: Int, buffer: ByteBuffer): Unit = { + append(getField(row, ordinal), buffer) + } /** - * Returns the size of the value. This is used to calculate the size of variable length types - * such as byte arrays and strings. + * Returns the size of the value `row(ordinal)`. This is used to calculate the size of variable + * length types such as byte arrays and strings. */ - def actualSize(v: JvmType): Int = defaultSize + def actualSize(row: Row, ordinal: Int): Int = defaultSize /** * Returns `row(ordinal)`. Subclasses should override this method to avoid boxing/unboxing costs @@ -67,7 +83,15 @@ private[sql] sealed abstract class ColumnType[T <: DataType, JvmType]( * Sets `row(ordinal)` to `field`. Subclasses should override this method to avoid boxing/unboxing * costs whenever possible. */ - def setField(row: MutableRow, ordinal: Int, value: JvmType) + def setField(row: MutableRow, ordinal: Int, value: JvmType): Unit + + /** + * Copies `from(fromOrdinal)` to `to(toOrdinal)`. Subclasses should override this method to avoid + * boxing/unboxing costs whenever possible. + */ + def copyField(from: Row, fromOrdinal: Int, to: MutableRow, toOrdinal: Int): Unit = { + to(toOrdinal) = from(fromOrdinal) + } /** * Creates a duplicated copy of the value. @@ -90,119 +114,205 @@ private[sql] abstract class NativeColumnType[T <: NativeType]( } private[sql] object INT extends NativeColumnType(IntegerType, 0, 4) { - def append(v: Int, buffer: ByteBuffer) { + def append(v: Int, buffer: ByteBuffer): Unit = { buffer.putInt(v) } + override def append(row: Row, ordinal: Int, buffer: ByteBuffer): Unit = { + buffer.putInt(row.getInt(ordinal)) + } + def extract(buffer: ByteBuffer) = { buffer.getInt() } - override def setField(row: MutableRow, ordinal: Int, value: Int) { + override def extract(buffer: ByteBuffer, row: MutableRow, ordinal: Int): Unit = { + row.setInt(ordinal, buffer.getInt()) + } + + override def setField(row: MutableRow, ordinal: Int, value: Int): Unit = { row.setInt(ordinal, value) } override def getField(row: Row, ordinal: Int) = row.getInt(ordinal) + + override def copyField(from: Row, fromOrdinal: Int, to: MutableRow, toOrdinal: Int): Unit = { + to.setInt(toOrdinal, from.getInt(fromOrdinal)) + } } private[sql] object LONG extends NativeColumnType(LongType, 1, 8) { - override def append(v: Long, buffer: ByteBuffer) { + override def append(v: Long, buffer: ByteBuffer): Unit = { buffer.putLong(v) } + override def append(row: Row, ordinal: Int, buffer: ByteBuffer): Unit = { + buffer.putLong(row.getLong(ordinal)) + } + override def extract(buffer: ByteBuffer) = { buffer.getLong() } - override def setField(row: MutableRow, ordinal: Int, value: Long) { + override def extract(buffer: ByteBuffer, row: MutableRow, ordinal: Int): Unit = { + row.setLong(ordinal, buffer.getLong()) + } + + override def setField(row: MutableRow, ordinal: Int, value: Long): Unit = { row.setLong(ordinal, value) } override def getField(row: Row, ordinal: Int) = row.getLong(ordinal) + + override def copyField(from: Row, fromOrdinal: Int, to: MutableRow, toOrdinal: Int): Unit = { + to.setLong(toOrdinal, from.getLong(fromOrdinal)) + } } private[sql] object FLOAT extends NativeColumnType(FloatType, 2, 4) { - override def append(v: Float, buffer: ByteBuffer) { + override def append(v: Float, buffer: ByteBuffer): Unit = { buffer.putFloat(v) } + override def append(row: Row, ordinal: Int, buffer: ByteBuffer): Unit = { + buffer.putFloat(row.getFloat(ordinal)) + } + override def extract(buffer: ByteBuffer) = { buffer.getFloat() } - override def setField(row: MutableRow, ordinal: Int, value: Float) { + override def extract(buffer: ByteBuffer, row: MutableRow, ordinal: Int): Unit = { + row.setFloat(ordinal, buffer.getFloat()) + } + + override def setField(row: MutableRow, ordinal: Int, value: Float): Unit = { row.setFloat(ordinal, value) } override def getField(row: Row, ordinal: Int) = row.getFloat(ordinal) + + override def copyField(from: Row, fromOrdinal: Int, to: MutableRow, toOrdinal: Int): Unit = { + to.setFloat(toOrdinal, from.getFloat(fromOrdinal)) + } } private[sql] object DOUBLE extends NativeColumnType(DoubleType, 3, 8) { - override def append(v: Double, buffer: ByteBuffer) { + override def append(v: Double, buffer: ByteBuffer): Unit = { buffer.putDouble(v) } + override def append(row: Row, ordinal: Int, buffer: ByteBuffer): Unit = { + buffer.putDouble(row.getDouble(ordinal)) + } + override def extract(buffer: ByteBuffer) = { buffer.getDouble() } - override def setField(row: MutableRow, ordinal: Int, value: Double) { + override def extract(buffer: ByteBuffer, row: MutableRow, ordinal: Int): Unit = { + row.setDouble(ordinal, buffer.getDouble()) + } + + override def setField(row: MutableRow, ordinal: Int, value: Double): Unit = { row.setDouble(ordinal, value) } override def getField(row: Row, ordinal: Int) = row.getDouble(ordinal) + + override def copyField(from: Row, fromOrdinal: Int, to: MutableRow, toOrdinal: Int): Unit = { + to.setDouble(toOrdinal, from.getDouble(fromOrdinal)) + } } private[sql] object BOOLEAN extends NativeColumnType(BooleanType, 4, 1) { - override def append(v: Boolean, buffer: ByteBuffer) { - buffer.put(if (v) 1.toByte else 0.toByte) + override def append(v: Boolean, buffer: ByteBuffer): Unit = { + buffer.put(if (v) 1: Byte else 0: Byte) + } + + override def append(row: Row, ordinal: Int, buffer: ByteBuffer): Unit = { + buffer.put(if (row.getBoolean(ordinal)) 1: Byte else 0: Byte) } override def extract(buffer: ByteBuffer) = buffer.get() == 1 - override def setField(row: MutableRow, ordinal: Int, value: Boolean) { + override def extract(buffer: ByteBuffer, row: MutableRow, ordinal: Int): Unit = { + row.setBoolean(ordinal, buffer.get() == 1) + } + + override def setField(row: MutableRow, ordinal: Int, value: Boolean): Unit = { row.setBoolean(ordinal, value) } override def getField(row: Row, ordinal: Int) = row.getBoolean(ordinal) + + override def copyField(from: Row, fromOrdinal: Int, to: MutableRow, toOrdinal: Int): Unit = { + to.setBoolean(toOrdinal, from.getBoolean(fromOrdinal)) + } } private[sql] object BYTE extends NativeColumnType(ByteType, 5, 1) { - override def append(v: Byte, buffer: ByteBuffer) { + override def append(v: Byte, buffer: ByteBuffer): Unit = { buffer.put(v) } + override def append(row: Row, ordinal: Int, buffer: ByteBuffer): Unit = { + buffer.put(row.getByte(ordinal)) + } + override def extract(buffer: ByteBuffer) = { buffer.get() } - override def setField(row: MutableRow, ordinal: Int, value: Byte) { + override def extract(buffer: ByteBuffer, row: MutableRow, ordinal: Int): Unit = { + row.setByte(ordinal, buffer.get()) + } + + override def setField(row: MutableRow, ordinal: Int, value: Byte): Unit = { row.setByte(ordinal, value) } override def getField(row: Row, ordinal: Int) = row.getByte(ordinal) + + override def copyField(from: Row, fromOrdinal: Int, to: MutableRow, toOrdinal: Int): Unit = { + to.setByte(toOrdinal, from.getByte(fromOrdinal)) + } } private[sql] object SHORT extends NativeColumnType(ShortType, 6, 2) { - override def append(v: Short, buffer: ByteBuffer) { + override def append(v: Short, buffer: ByteBuffer): Unit = { buffer.putShort(v) } + override def append(row: Row, ordinal: Int, buffer: ByteBuffer): Unit = { + buffer.putShort(row.getShort(ordinal)) + } + override def extract(buffer: ByteBuffer) = { buffer.getShort() } - override def setField(row: MutableRow, ordinal: Int, value: Short) { + override def extract(buffer: ByteBuffer, row: MutableRow, ordinal: Int): Unit = { + row.setShort(ordinal, buffer.getShort()) + } + + override def setField(row: MutableRow, ordinal: Int, value: Short): Unit = { row.setShort(ordinal, value) } override def getField(row: Row, ordinal: Int) = row.getShort(ordinal) + + override def copyField(from: Row, fromOrdinal: Int, to: MutableRow, toOrdinal: Int): Unit = { + to.setShort(toOrdinal, from.getShort(fromOrdinal)) + } } private[sql] object STRING extends NativeColumnType(StringType, 7, 8) { - override def actualSize(v: String): Int = v.getBytes("utf-8").length + 4 + override def actualSize(row: Row, ordinal: Int): Int = { + row.getString(ordinal).getBytes("utf-8").length + 4 + } - override def append(v: String, buffer: ByteBuffer) { + override def append(v: String, buffer: ByteBuffer): Unit = { val stringBytes = v.getBytes("utf-8") buffer.putInt(stringBytes.length).put(stringBytes, 0, stringBytes.length) } @@ -214,11 +324,15 @@ private[sql] object STRING extends NativeColumnType(StringType, 7, 8) { new String(stringBytes, "utf-8") } - override def setField(row: MutableRow, ordinal: Int, value: String) { + override def setField(row: MutableRow, ordinal: Int, value: String): Unit = { row.setString(ordinal, value) } override def getField(row: Row, ordinal: Int) = row.getString(ordinal) + + override def copyField(from: Row, fromOrdinal: Int, to: MutableRow, toOrdinal: Int): Unit = { + to.setString(toOrdinal, from.getString(fromOrdinal)) + } } private[sql] object TIMESTAMP extends NativeColumnType(TimestampType, 8, 12) { @@ -228,7 +342,7 @@ private[sql] object TIMESTAMP extends NativeColumnType(TimestampType, 8, 12) { timestamp } - override def append(v: Timestamp, buffer: ByteBuffer) { + override def append(v: Timestamp, buffer: ByteBuffer): Unit = { buffer.putLong(v.getTime).putInt(v.getNanos) } @@ -236,7 +350,7 @@ private[sql] object TIMESTAMP extends NativeColumnType(TimestampType, 8, 12) { row(ordinal).asInstanceOf[Timestamp] } - override def setField(row: MutableRow, ordinal: Int, value: Timestamp) { + override def setField(row: MutableRow, ordinal: Int, value: Timestamp): Unit = { row(ordinal) = value } } @@ -246,9 +360,11 @@ private[sql] sealed abstract class ByteArrayColumnType[T <: DataType]( defaultSize: Int) extends ColumnType[T, Array[Byte]](typeId, defaultSize) { - override def actualSize(v: Array[Byte]) = v.length + 4 + override def actualSize(row: Row, ordinal: Int) = { + getField(row, ordinal).length + 4 + } - override def append(v: Array[Byte], buffer: ByteBuffer) { + override def append(v: Array[Byte], buffer: ByteBuffer): Unit = { buffer.putInt(v.length).put(v, 0, v.length) } @@ -261,7 +377,7 @@ private[sql] sealed abstract class ByteArrayColumnType[T <: DataType]( } private[sql] object BINARY extends ByteArrayColumnType[BinaryType.type](9, 16) { - override def setField(row: MutableRow, ordinal: Int, value: Array[Byte]) { + override def setField(row: MutableRow, ordinal: Int, value: Array[Byte]): Unit = { row(ordinal) = value } @@ -272,7 +388,7 @@ private[sql] object BINARY extends ByteArrayColumnType[BinaryType.type](9, 16) { // serialized first before appending to the column `ByteBuffer`, and is also extracted as serialized // byte array. private[sql] object GENERIC extends ByteArrayColumnType[DataType](10, 16) { - override def setField(row: MutableRow, ordinal: Int, value: Array[Byte]) { + override def setField(row: MutableRow, ordinal: Int, value: Array[Byte]): Unit = { row(ordinal) = SparkSqlSerializer.deserialize[Any](value) } diff --git a/sql/core/src/main/scala/org/apache/spark/sql/columnar/InMemoryColumnarTableScan.scala b/sql/core/src/main/scala/org/apache/spark/sql/columnar/InMemoryColumnarTableScan.scala index 6eab2f23c18e1..8a3612cdf19be 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/columnar/InMemoryColumnarTableScan.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/columnar/InMemoryColumnarTableScan.scala @@ -52,7 +52,7 @@ private[sql] case class InMemoryRelation( // As in Spark, the actual work of caching is lazy. if (_cachedColumnBuffers == null) { val output = child.output - val cached = child.execute().mapPartitions { baseIterator => + val cached = child.execute().mapPartitions { rowIterator => new Iterator[CachedBatch] { def next() = { val columnBuilders = output.map { attribute => @@ -61,11 +61,9 @@ private[sql] case class InMemoryRelation( ColumnBuilder(columnType.typeId, initialBufferSize, attribute.name, useCompression) }.toArray - var row: Row = null var rowCount = 0 - - while (baseIterator.hasNext && rowCount < batchSize) { - row = baseIterator.next() + while (rowIterator.hasNext && rowCount < batchSize) { + val row = rowIterator.next() var i = 0 while (i < row.length) { columnBuilders(i).appendFrom(row, i) @@ -80,7 +78,7 @@ private[sql] case class InMemoryRelation( CachedBatch(columnBuilders.map(_.build()), stats) } - def hasNext = baseIterator.hasNext + def hasNext = rowIterator.hasNext } }.cache() @@ -182,6 +180,7 @@ private[sql] case class InMemoryColumnarTableScan( } } + // Accumulators used for testing purposes val readPartitions = sparkContext.accumulator(0) val readBatches = sparkContext.accumulator(0) @@ -191,40 +190,36 @@ private[sql] case class InMemoryColumnarTableScan( readPartitions.setValue(0) readBatches.setValue(0) - relation.cachedColumnBuffers.mapPartitions { iterator => + relation.cachedColumnBuffers.mapPartitions { cachedBatchIterator => val partitionFilter = newPredicate( partitionFilters.reduceOption(And).getOrElse(Literal(true)), relation.partitionStatistics.schema) - // Find the ordinals of the requested columns. If none are requested, use the first. - val requestedColumns = if (attributes.isEmpty) { - Seq(0) + // Find the ordinals and data types of the requested columns. If none are requested, use the + // narrowest (the field with minimum default element size). + val (requestedColumnIndices, requestedColumnDataTypes) = if (attributes.isEmpty) { + val (narrowestOrdinal, narrowestDataType) = + relation.output.zipWithIndex.map { case (a, ordinal) => + ordinal -> a.dataType + } minBy { case (_, dataType) => + ColumnType(dataType).defaultSize + } + Seq(narrowestOrdinal) -> Seq(narrowestDataType) } else { - attributes.map(a => relation.output.indexWhere(_.exprId == a.exprId)) + attributes.map { a => + relation.output.indexWhere(_.exprId == a.exprId) -> a.dataType + }.unzip } - val rows = iterator - // Skip pruned batches - .filter { cachedBatch => - if (inMemoryPartitionPruningEnabled && !partitionFilter(cachedBatch.stats)) { - def statsString = relation.partitionStatistics.schema - .zip(cachedBatch.stats) - .map { case (a, s) => s"${a.name}: $s" } - .mkString(", ") - logInfo(s"Skipping partition based on stats $statsString") - false - } else { - readBatches += 1 - true - } - } - // Build column accessors - .map { cachedBatch => - requestedColumns.map(cachedBatch.buffers(_)).map(ColumnAccessor(_)) - } - // Extract rows via column accessors - .flatMap { columnAccessors => - val nextRow = new GenericMutableRow(columnAccessors.length) + val nextRow = new SpecificMutableRow(requestedColumnDataTypes) + + def cachedBatchesToRows(cacheBatches: Iterator[CachedBatch]) = { + val rows = cacheBatches.flatMap { cachedBatch => + // Build column accessors + val columnAccessors = + requestedColumnIndices.map(cachedBatch.buffers(_)).map(ColumnAccessor(_)) + + // Extract rows via column accessors new Iterator[Row] { override def next() = { var i = 0 @@ -235,15 +230,38 @@ private[sql] case class InMemoryColumnarTableScan( nextRow } - override def hasNext = columnAccessors.head.hasNext + override def hasNext = columnAccessors(0).hasNext } } - if (rows.hasNext) { - readPartitions += 1 + if (rows.hasNext) { + readPartitions += 1 + } + + rows } - rows + // Do partition batch pruning if enabled + val cachedBatchesToScan = + if (inMemoryPartitionPruningEnabled) { + cachedBatchIterator.filter { cachedBatch => + if (!partitionFilter(cachedBatch.stats)) { + def statsString = relation.partitionStatistics.schema + .zip(cachedBatch.stats) + .map { case (a, s) => s"${a.name}: $s" } + .mkString(", ") + logInfo(s"Skipping partition based on stats $statsString") + false + } else { + readBatches += 1 + true + } + } + } else { + cachedBatchIterator + } + + cachedBatchesToRows(cachedBatchesToScan) } } } diff --git a/sql/core/src/main/scala/org/apache/spark/sql/columnar/NullableColumnAccessor.scala b/sql/core/src/main/scala/org/apache/spark/sql/columnar/NullableColumnAccessor.scala index b7f8826861a2c..965782a40031b 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/columnar/NullableColumnAccessor.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/columnar/NullableColumnAccessor.scala @@ -29,7 +29,7 @@ private[sql] trait NullableColumnAccessor extends ColumnAccessor { private var nextNullIndex: Int = _ private var pos: Int = 0 - abstract override protected def initialize() { + abstract override protected def initialize(): Unit = { nullsBuffer = underlyingBuffer.duplicate().order(ByteOrder.nativeOrder()) nullCount = nullsBuffer.getInt() nextNullIndex = if (nullCount > 0) nullsBuffer.getInt() else -1 @@ -39,7 +39,7 @@ private[sql] trait NullableColumnAccessor extends ColumnAccessor { super.initialize() } - abstract override def extractTo(row: MutableRow, ordinal: Int) { + abstract override def extractTo(row: MutableRow, ordinal: Int): Unit = { if (pos == nextNullIndex) { seenNulls += 1 diff --git a/sql/core/src/main/scala/org/apache/spark/sql/columnar/NullableColumnBuilder.scala b/sql/core/src/main/scala/org/apache/spark/sql/columnar/NullableColumnBuilder.scala index a72970eef7aa4..f1f494ac26d0c 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/columnar/NullableColumnBuilder.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/columnar/NullableColumnBuilder.scala @@ -40,7 +40,11 @@ private[sql] trait NullableColumnBuilder extends ColumnBuilder { protected var nullCount: Int = _ private var pos: Int = _ - abstract override def initialize(initialSize: Int, columnName: String, useCompression: Boolean) { + abstract override def initialize( + initialSize: Int, + columnName: String, + useCompression: Boolean): Unit = { + nulls = ByteBuffer.allocate(1024) nulls.order(ByteOrder.nativeOrder()) pos = 0 @@ -48,7 +52,7 @@ private[sql] trait NullableColumnBuilder extends ColumnBuilder { super.initialize(initialSize, columnName, useCompression) } - abstract override def appendFrom(row: Row, ordinal: Int) { + abstract override def appendFrom(row: Row, ordinal: Int): Unit = { columnStats.gatherStats(row, ordinal) if (row.isNullAt(ordinal)) { nulls = ColumnBuilder.ensureFreeSpace(nulls, 4) diff --git a/sql/core/src/main/scala/org/apache/spark/sql/columnar/compression/CompressibleColumnAccessor.scala b/sql/core/src/main/scala/org/apache/spark/sql/columnar/compression/CompressibleColumnAccessor.scala index b4120a3d4368b..27ac5f4dbdbbc 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/columnar/compression/CompressibleColumnAccessor.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/columnar/compression/CompressibleColumnAccessor.scala @@ -17,8 +17,7 @@ package org.apache.spark.sql.columnar.compression -import java.nio.ByteBuffer - +import org.apache.spark.sql.catalyst.expressions.MutableRow import org.apache.spark.sql.catalyst.types.NativeType import org.apache.spark.sql.columnar.{ColumnAccessor, NativeColumnAccessor} @@ -34,5 +33,7 @@ private[sql] trait CompressibleColumnAccessor[T <: NativeType] extends ColumnAcc abstract override def hasNext = super.hasNext || decoder.hasNext - override def extractSingle(buffer: ByteBuffer): T#JvmType = decoder.next() + override def extractSingle(row: MutableRow, ordinal: Int): Unit = { + decoder.next(row, ordinal) + } } diff --git a/sql/core/src/main/scala/org/apache/spark/sql/columnar/compression/CompressibleColumnBuilder.scala b/sql/core/src/main/scala/org/apache/spark/sql/columnar/compression/CompressibleColumnBuilder.scala index a5826bb033e41..628d9cec41d6b 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/columnar/compression/CompressibleColumnBuilder.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/columnar/compression/CompressibleColumnBuilder.scala @@ -48,12 +48,16 @@ private[sql] trait CompressibleColumnBuilder[T <: NativeType] var compressionEncoders: Seq[Encoder[T]] = _ - abstract override def initialize(initialSize: Int, columnName: String, useCompression: Boolean) { + abstract override def initialize( + initialSize: Int, + columnName: String, + useCompression: Boolean): Unit = { + compressionEncoders = if (useCompression) { - schemes.filter(_.supports(columnType)).map(_.encoder[T]) + schemes.filter(_.supports(columnType)).map(_.encoder[T](columnType)) } else { - Seq(PassThrough.encoder) + Seq(PassThrough.encoder(columnType)) } super.initialize(initialSize, columnName, useCompression) } @@ -62,17 +66,15 @@ private[sql] trait CompressibleColumnBuilder[T <: NativeType] encoder.compressionRatio < 0.8 } - private def gatherCompressibilityStats(row: Row, ordinal: Int) { - val field = columnType.getField(row, ordinal) - + private def gatherCompressibilityStats(row: Row, ordinal: Int): Unit = { var i = 0 while (i < compressionEncoders.length) { - compressionEncoders(i).gatherCompressibilityStats(field, columnType) + compressionEncoders(i).gatherCompressibilityStats(row, ordinal) i += 1 } } - abstract override def appendFrom(row: Row, ordinal: Int) { + abstract override def appendFrom(row: Row, ordinal: Int): Unit = { super.appendFrom(row, ordinal) if (!row.isNullAt(ordinal)) { gatherCompressibilityStats(row, ordinal) @@ -84,7 +86,7 @@ private[sql] trait CompressibleColumnBuilder[T <: NativeType] val typeId = nonNullBuffer.getInt() val encoder: Encoder[T] = { val candidate = compressionEncoders.minBy(_.compressionRatio) - if (isWorthCompressing(candidate)) candidate else PassThrough.encoder + if (isWorthCompressing(candidate)) candidate else PassThrough.encoder(columnType) } // Header = column type ID + null count + null positions @@ -104,7 +106,7 @@ private[sql] trait CompressibleColumnBuilder[T <: NativeType] .putInt(nullCount) .put(nulls) - logInfo(s"Compressor for [$columnName]: $encoder, ratio: ${encoder.compressionRatio}") - encoder.compress(nonNullBuffer, compressedBuffer, columnType) + logDebug(s"Compressor for [$columnName]: $encoder, ratio: ${encoder.compressionRatio}") + encoder.compress(nonNullBuffer, compressedBuffer) } } diff --git a/sql/core/src/main/scala/org/apache/spark/sql/columnar/compression/CompressionScheme.scala b/sql/core/src/main/scala/org/apache/spark/sql/columnar/compression/CompressionScheme.scala index 7797f75177893..acb06cb5376b4 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/columnar/compression/CompressionScheme.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/columnar/compression/CompressionScheme.scala @@ -17,13 +17,15 @@ package org.apache.spark.sql.columnar.compression -import java.nio.{ByteOrder, ByteBuffer} +import java.nio.{ByteBuffer, ByteOrder} +import org.apache.spark.sql.Row +import org.apache.spark.sql.catalyst.expressions.MutableRow import org.apache.spark.sql.catalyst.types.NativeType import org.apache.spark.sql.columnar.{ColumnType, NativeColumnType} private[sql] trait Encoder[T <: NativeType] { - def gatherCompressibilityStats(value: T#JvmType, columnType: NativeColumnType[T]) {} + def gatherCompressibilityStats(row: Row, ordinal: Int): Unit = {} def compressedSize: Int @@ -33,17 +35,21 @@ private[sql] trait Encoder[T <: NativeType] { if (uncompressedSize > 0) compressedSize.toDouble / uncompressedSize else 1.0 } - def compress(from: ByteBuffer, to: ByteBuffer, columnType: NativeColumnType[T]): ByteBuffer + def compress(from: ByteBuffer, to: ByteBuffer): ByteBuffer } -private[sql] trait Decoder[T <: NativeType] extends Iterator[T#JvmType] +private[sql] trait Decoder[T <: NativeType] { + def next(row: MutableRow, ordinal: Int): Unit + + def hasNext: Boolean +} private[sql] trait CompressionScheme { def typeId: Int def supports(columnType: ColumnType[_, _]): Boolean - def encoder[T <: NativeType]: Encoder[T] + def encoder[T <: NativeType](columnType: NativeColumnType[T]): Encoder[T] def decoder[T <: NativeType](buffer: ByteBuffer, columnType: NativeColumnType[T]): Decoder[T] } diff --git a/sql/core/src/main/scala/org/apache/spark/sql/columnar/compression/compressionSchemes.scala b/sql/core/src/main/scala/org/apache/spark/sql/columnar/compression/compressionSchemes.scala index 8cf9ec74ca2de..29edcf17242c5 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/columnar/compression/compressionSchemes.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/columnar/compression/compressionSchemes.scala @@ -23,7 +23,8 @@ import scala.collection.mutable import scala.reflect.ClassTag import scala.reflect.runtime.universe.runtimeMirror -import org.apache.spark.sql.catalyst.expressions.GenericMutableRow +import org.apache.spark.sql.Row +import org.apache.spark.sql.catalyst.expressions.{MutableRow, SpecificMutableRow} import org.apache.spark.sql.catalyst.types._ import org.apache.spark.sql.columnar._ import org.apache.spark.util.Utils @@ -33,18 +34,20 @@ private[sql] case object PassThrough extends CompressionScheme { override def supports(columnType: ColumnType[_, _]) = true - override def encoder[T <: NativeType] = new this.Encoder[T] + override def encoder[T <: NativeType](columnType: NativeColumnType[T]) = { + new this.Encoder[T](columnType) + } override def decoder[T <: NativeType](buffer: ByteBuffer, columnType: NativeColumnType[T]) = { new this.Decoder(buffer, columnType) } - class Encoder[T <: NativeType] extends compression.Encoder[T] { + class Encoder[T <: NativeType](columnType: NativeColumnType[T]) extends compression.Encoder[T] { override def uncompressedSize = 0 override def compressedSize = 0 - override def compress(from: ByteBuffer, to: ByteBuffer, columnType: NativeColumnType[T]) = { + override def compress(from: ByteBuffer, to: ByteBuffer) = { // Writes compression type ID and copies raw contents to.putInt(PassThrough.typeId).put(from).rewind() to @@ -54,7 +57,9 @@ private[sql] case object PassThrough extends CompressionScheme { class Decoder[T <: NativeType](buffer: ByteBuffer, columnType: NativeColumnType[T]) extends compression.Decoder[T] { - override def next() = columnType.extract(buffer) + override def next(row: MutableRow, ordinal: Int): Unit = { + columnType.extract(buffer, row, ordinal) + } override def hasNext = buffer.hasRemaining } @@ -63,7 +68,9 @@ private[sql] case object PassThrough extends CompressionScheme { private[sql] case object RunLengthEncoding extends CompressionScheme { override val typeId = 1 - override def encoder[T <: NativeType] = new this.Encoder[T] + override def encoder[T <: NativeType](columnType: NativeColumnType[T]) = { + new this.Encoder[T](columnType) + } override def decoder[T <: NativeType](buffer: ByteBuffer, columnType: NativeColumnType[T]) = { new this.Decoder(buffer, columnType) @@ -74,24 +81,25 @@ private[sql] case object RunLengthEncoding extends CompressionScheme { case _ => false } - class Encoder[T <: NativeType] extends compression.Encoder[T] { + class Encoder[T <: NativeType](columnType: NativeColumnType[T]) extends compression.Encoder[T] { private var _uncompressedSize = 0 private var _compressedSize = 0 // Using `MutableRow` to store the last value to avoid boxing/unboxing cost. - private val lastValue = new GenericMutableRow(1) + private val lastValue = new SpecificMutableRow(Seq(columnType.dataType)) private var lastRun = 0 override def uncompressedSize = _uncompressedSize override def compressedSize = _compressedSize - override def gatherCompressibilityStats(value: T#JvmType, columnType: NativeColumnType[T]) { - val actualSize = columnType.actualSize(value) + override def gatherCompressibilityStats(row: Row, ordinal: Int): Unit = { + val value = columnType.getField(row, ordinal) + val actualSize = columnType.actualSize(row, ordinal) _uncompressedSize += actualSize if (lastValue.isNullAt(0)) { - columnType.setField(lastValue, 0, value) + columnType.copyField(row, ordinal, lastValue, 0) lastRun = 1 _compressedSize += actualSize + 4 } else { @@ -99,37 +107,40 @@ private[sql] case object RunLengthEncoding extends CompressionScheme { lastRun += 1 } else { _compressedSize += actualSize + 4 - columnType.setField(lastValue, 0, value) + columnType.copyField(row, ordinal, lastValue, 0) lastRun = 1 } } } - override def compress(from: ByteBuffer, to: ByteBuffer, columnType: NativeColumnType[T]) = { + override def compress(from: ByteBuffer, to: ByteBuffer) = { to.putInt(RunLengthEncoding.typeId) if (from.hasRemaining) { - var currentValue = columnType.extract(from) + val currentValue = new SpecificMutableRow(Seq(columnType.dataType)) var currentRun = 1 + val value = new SpecificMutableRow(Seq(columnType.dataType)) + + columnType.extract(from, currentValue, 0) while (from.hasRemaining) { - val value = columnType.extract(from) + columnType.extract(from, value, 0) - if (value == currentValue) { + if (value.head == currentValue.head) { currentRun += 1 } else { // Writes current run - columnType.append(currentValue, to) + columnType.append(currentValue, 0, to) to.putInt(currentRun) // Resets current run - currentValue = value + columnType.copyField(value, 0, currentValue, 0) currentRun = 1 } } // Writes the last run - columnType.append(currentValue, to) + columnType.append(currentValue, 0, to) to.putInt(currentRun) } @@ -145,7 +156,7 @@ private[sql] case object RunLengthEncoding extends CompressionScheme { private var valueCount = 0 private var currentValue: T#JvmType = _ - override def next() = { + override def next(row: MutableRow, ordinal: Int): Unit = { if (valueCount == run) { currentValue = columnType.extract(buffer) run = buffer.getInt() @@ -154,7 +165,7 @@ private[sql] case object RunLengthEncoding extends CompressionScheme { valueCount += 1 } - currentValue + columnType.setField(row, ordinal, currentValue) } override def hasNext = valueCount < run || buffer.hasRemaining @@ -171,14 +182,16 @@ private[sql] case object DictionaryEncoding extends CompressionScheme { new this.Decoder(buffer, columnType) } - override def encoder[T <: NativeType] = new this.Encoder[T] + override def encoder[T <: NativeType](columnType: NativeColumnType[T]) = { + new this.Encoder[T](columnType) + } override def supports(columnType: ColumnType[_, _]) = columnType match { case INT | LONG | STRING => true case _ => false } - class Encoder[T <: NativeType] extends compression.Encoder[T] { + class Encoder[T <: NativeType](columnType: NativeColumnType[T]) extends compression.Encoder[T] { // Size of the input, uncompressed, in bytes. Note that we only count until the dictionary // overflows. private var _uncompressedSize = 0 @@ -200,9 +213,11 @@ private[sql] case object DictionaryEncoding extends CompressionScheme { // to store dictionary element count. private var dictionarySize = 4 - override def gatherCompressibilityStats(value: T#JvmType, columnType: NativeColumnType[T]) { + override def gatherCompressibilityStats(row: Row, ordinal: Int): Unit = { + val value = columnType.getField(row, ordinal) + if (!overflow) { - val actualSize = columnType.actualSize(value) + val actualSize = columnType.actualSize(row, ordinal) count += 1 _uncompressedSize += actualSize @@ -221,7 +236,7 @@ private[sql] case object DictionaryEncoding extends CompressionScheme { } } - override def compress(from: ByteBuffer, to: ByteBuffer, columnType: NativeColumnType[T]) = { + override def compress(from: ByteBuffer, to: ByteBuffer) = { if (overflow) { throw new IllegalStateException( "Dictionary encoding should not be used because of dictionary overflow.") @@ -264,7 +279,9 @@ private[sql] case object DictionaryEncoding extends CompressionScheme { } } - override def next() = dictionary(buffer.getShort()) + override def next(row: MutableRow, ordinal: Int): Unit = { + columnType.setField(row, ordinal, dictionary(buffer.getShort())) + } override def hasNext = buffer.hasRemaining } @@ -279,25 +296,20 @@ private[sql] case object BooleanBitSet extends CompressionScheme { new this.Decoder(buffer).asInstanceOf[compression.Decoder[T]] } - override def encoder[T <: NativeType] = (new this.Encoder).asInstanceOf[compression.Encoder[T]] + override def encoder[T <: NativeType](columnType: NativeColumnType[T]) = { + (new this.Encoder).asInstanceOf[compression.Encoder[T]] + } override def supports(columnType: ColumnType[_, _]) = columnType == BOOLEAN class Encoder extends compression.Encoder[BooleanType.type] { private var _uncompressedSize = 0 - override def gatherCompressibilityStats( - value: Boolean, - columnType: NativeColumnType[BooleanType.type]) { - + override def gatherCompressibilityStats(row: Row, ordinal: Int): Unit = { _uncompressedSize += BOOLEAN.defaultSize } - override def compress( - from: ByteBuffer, - to: ByteBuffer, - columnType: NativeColumnType[BooleanType.type]) = { - + override def compress(from: ByteBuffer, to: ByteBuffer) = { to.putInt(BooleanBitSet.typeId) // Total element count (1 byte per Boolean value) .putInt(from.remaining) @@ -349,7 +361,7 @@ private[sql] case object BooleanBitSet extends CompressionScheme { private var visited: Int = 0 - override def next(): Boolean = { + override def next(row: MutableRow, ordinal: Int): Unit = { val bit = visited % BITS_PER_LONG visited += 1 @@ -357,123 +369,167 @@ private[sql] case object BooleanBitSet extends CompressionScheme { currentWord = buffer.getLong() } - ((currentWord >> bit) & 1) != 0 + row.setBoolean(ordinal, ((currentWord >> bit) & 1) != 0) } override def hasNext: Boolean = visited < count } } -private[sql] sealed abstract class IntegralDelta[I <: IntegralType] extends CompressionScheme { +private[sql] case object IntDelta extends CompressionScheme { + override def typeId: Int = 4 + override def decoder[T <: NativeType](buffer: ByteBuffer, columnType: NativeColumnType[T]) = { - new this.Decoder(buffer, columnType.asInstanceOf[NativeColumnType[I]]) - .asInstanceOf[compression.Decoder[T]] + new Decoder(buffer, INT).asInstanceOf[compression.Decoder[T]] } - override def encoder[T <: NativeType] = (new this.Encoder).asInstanceOf[compression.Encoder[T]] - - /** - * Computes `delta = x - y`, returns `(true, delta)` if `delta` can fit into a single byte, or - * `(false, 0: Byte)` otherwise. - */ - protected def byteSizedDelta(x: I#JvmType, y: I#JvmType): (Boolean, Byte) + override def encoder[T <: NativeType](columnType: NativeColumnType[T]) = { + (new Encoder).asInstanceOf[compression.Encoder[T]] + } - /** - * Simply computes `x + delta` - */ - protected def addDelta(x: I#JvmType, delta: Byte): I#JvmType + override def supports(columnType: ColumnType[_, _]) = columnType == INT - class Encoder extends compression.Encoder[I] { - private var _compressedSize: Int = 0 + class Encoder extends compression.Encoder[IntegerType.type] { + protected var _compressedSize: Int = 0 + protected var _uncompressedSize: Int = 0 - private var _uncompressedSize: Int = 0 + override def compressedSize = _compressedSize + override def uncompressedSize = _uncompressedSize - private var prev: I#JvmType = _ + private var prevValue: Int = _ - private var initial = true + override def gatherCompressibilityStats(row: Row, ordinal: Int): Unit = { + val value = row.getInt(ordinal) + val delta = value - prevValue - override def gatherCompressibilityStats(value: I#JvmType, columnType: NativeColumnType[I]) { - _uncompressedSize += columnType.defaultSize + _compressedSize += 1 - if (initial) { - initial = false - _compressedSize += 1 + columnType.defaultSize - } else { - val (smallEnough, _) = byteSizedDelta(value, prev) - _compressedSize += (if (smallEnough) 1 else 1 + columnType.defaultSize) + // If this is the first integer to be compressed, or the delta is out of byte range, then give + // up compressing this integer. + if (_uncompressedSize == 0 || delta <= Byte.MinValue || delta > Byte.MaxValue) { + _compressedSize += INT.defaultSize } - prev = value + _uncompressedSize += INT.defaultSize + prevValue = value } - override def compress(from: ByteBuffer, to: ByteBuffer, columnType: NativeColumnType[I]) = { + override def compress(from: ByteBuffer, to: ByteBuffer): ByteBuffer = { to.putInt(typeId) if (from.hasRemaining) { - var prev = columnType.extract(from) + var prev = from.getInt() to.put(Byte.MinValue) - columnType.append(prev, to) + to.putInt(prev) while (from.hasRemaining) { - val current = columnType.extract(from) - val (smallEnough, delta) = byteSizedDelta(current, prev) + val current = from.getInt() + val delta = current - prev prev = current - if (smallEnough) { - to.put(delta) + if (Byte.MinValue < delta && delta <= Byte.MaxValue) { + to.put(delta.toByte) } else { to.put(Byte.MinValue) - columnType.append(current, to) + to.putInt(current) } } } - to.rewind() - to + to.rewind().asInstanceOf[ByteBuffer] } - - override def uncompressedSize = _uncompressedSize - - override def compressedSize = _compressedSize } - class Decoder(buffer: ByteBuffer, columnType: NativeColumnType[I]) - extends compression.Decoder[I] { + class Decoder(buffer: ByteBuffer, columnType: NativeColumnType[IntegerType.type]) + extends compression.Decoder[IntegerType.type] { + + private var prev: Int = _ - private var prev: I#JvmType = _ + override def hasNext: Boolean = buffer.hasRemaining - override def next() = { + override def next(row: MutableRow, ordinal: Int): Unit = { val delta = buffer.get() - prev = if (delta > Byte.MinValue) addDelta(prev, delta) else columnType.extract(buffer) - prev + prev = if (delta > Byte.MinValue) prev + delta else buffer.getInt() + row.setInt(ordinal, prev) } - - override def hasNext = buffer.hasRemaining } } -private[sql] case object IntDelta extends IntegralDelta[IntegerType.type] { - override val typeId = 4 +private[sql] case object LongDelta extends CompressionScheme { + override def typeId: Int = 5 - override def supports(columnType: ColumnType[_, _]) = columnType == INT + override def decoder[T <: NativeType](buffer: ByteBuffer, columnType: NativeColumnType[T]) = { + new Decoder(buffer, LONG).asInstanceOf[compression.Decoder[T]] + } + + override def encoder[T <: NativeType](columnType: NativeColumnType[T]) = { + (new Encoder).asInstanceOf[compression.Encoder[T]] + } - override protected def addDelta(x: Int, delta: Byte) = x + delta + override def supports(columnType: ColumnType[_, _]) = columnType == LONG + + class Encoder extends compression.Encoder[LongType.type] { + protected var _compressedSize: Int = 0 + protected var _uncompressedSize: Int = 0 + + override def compressedSize = _compressedSize + override def uncompressedSize = _uncompressedSize + + private var prevValue: Long = _ + + override def gatherCompressibilityStats(row: Row, ordinal: Int): Unit = { + val value = row.getLong(ordinal) + val delta = value - prevValue + + _compressedSize += 1 - override protected def byteSizedDelta(x: Int, y: Int): (Boolean, Byte) = { - val delta = x - y - if (math.abs(delta) <= Byte.MaxValue) (true, delta.toByte) else (false, 0: Byte) + // If this is the first long integer to be compressed, or the delta is out of byte range, then + // give up compressing this long integer. + if (_uncompressedSize == 0 || delta <= Byte.MinValue || delta > Byte.MaxValue) { + _compressedSize += LONG.defaultSize + } + + _uncompressedSize += LONG.defaultSize + prevValue = value + } + + override def compress(from: ByteBuffer, to: ByteBuffer): ByteBuffer = { + to.putInt(typeId) + + if (from.hasRemaining) { + var prev = from.getLong() + to.put(Byte.MinValue) + to.putLong(prev) + + while (from.hasRemaining) { + val current = from.getLong() + val delta = current - prev + prev = current + + if (Byte.MinValue < delta && delta <= Byte.MaxValue) { + to.put(delta.toByte) + } else { + to.put(Byte.MinValue) + to.putLong(current) + } + } + } + + to.rewind().asInstanceOf[ByteBuffer] + } } -} -private[sql] case object LongDelta extends IntegralDelta[LongType.type] { - override val typeId = 5 + class Decoder(buffer: ByteBuffer, columnType: NativeColumnType[LongType.type]) + extends compression.Decoder[LongType.type] { - override def supports(columnType: ColumnType[_, _]) = columnType == LONG + private var prev: Long = _ - override protected def addDelta(x: Long, delta: Byte) = x + delta + override def hasNext: Boolean = buffer.hasRemaining - override protected def byteSizedDelta(x: Long, y: Long): (Boolean, Byte) = { - val delta = x - y - if (math.abs(delta) <= Byte.MaxValue) (true, delta.toByte) else (false, 0: Byte) + override def next(row: MutableRow, ordinal: Int): Unit = { + val delta = buffer.get() + prev = if (delta > Byte.MinValue) prev + delta else buffer.getLong() + row.setLong(ordinal, prev) + } } } diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala index 7943d6e1b6fb5..45687d960404c 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala @@ -305,6 +305,8 @@ private[sql] abstract class SparkStrategies extends QueryPlanner[SparkPlan] { Seq(execution.ExplainCommand(logicalPlan, plan.output, extended)(context)) case logical.CacheCommand(tableName, cache) => Seq(execution.CacheCommand(tableName, cache)(context)) + case logical.CacheTableAsSelectCommand(tableName, plan) => + Seq(execution.CacheTableAsSelectCommand(tableName, plan)) case _ => Nil } } diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/commands.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/commands.scala index 94543fc95b470..1535291f7908b 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/commands.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/commands.scala @@ -166,3 +166,22 @@ case class DescribeCommand(child: SparkPlan, output: Seq[Attribute])( child.output.map(field => Row(field.name, field.dataType.toString, null)) } } + +/** + * :: DeveloperApi :: + */ +@DeveloperApi +case class CacheTableAsSelectCommand(tableName: String, plan: LogicalPlan) + extends LeafNode with Command { + + override protected[sql] lazy val sideEffectResult = { + sqlContext.catalog.registerTable(None, tableName, sqlContext.executePlan(plan).analyzed) + sqlContext.cacheTable(tableName) + // It does the caching eager. + sqlContext.table(tableName).count + Seq.empty[Row] + } + + override def output: Seq[Attribute] = Seq.empty + +} diff --git a/sql/core/src/main/scala/org/apache/spark/sql/test/TestSQLContext.scala b/sql/core/src/main/scala/org/apache/spark/sql/test/TestSQLContext.scala index f2389f8f0591e..265b67737c475 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/test/TestSQLContext.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/test/TestSQLContext.scala @@ -18,8 +18,13 @@ package org.apache.spark.sql.test import org.apache.spark.{SparkConf, SparkContext} -import org.apache.spark.sql.SQLContext +import org.apache.spark.sql.{SQLConf, SQLContext} /** A SQLContext that can be used for local testing. */ object TestSQLContext - extends SQLContext(new SparkContext("local", "TestSQLContext", new SparkConf())) + extends SQLContext(new SparkContext("local[2]", "TestSQLContext", new SparkConf())) { + + /** Fewer partitions to speed up testing. */ + override private[spark] def numShufflePartitions: Int = + getConf(SQLConf.SHUFFLE_PARTITIONS, "5").toInt +} diff --git a/sql/core/src/test/scala/org/apache/spark/sql/CachedTableSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/CachedTableSuite.scala index befef46d93973..591592841e9fe 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/CachedTableSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/CachedTableSuite.scala @@ -119,4 +119,17 @@ class CachedTableSuite extends QueryTest { } assert(!TestSQLContext.isCached("testData"), "Table 'testData' should not be cached") } + + test("CACHE TABLE tableName AS SELECT Star Table") { + TestSQLContext.sql("CACHE TABLE testCacheTable AS SELECT * FROM testData") + TestSQLContext.sql("SELECT * FROM testCacheTable WHERE key = 1").collect() + assert(TestSQLContext.isCached("testCacheTable"), "Table 'testCacheTable' should be cached") + TestSQLContext.uncacheTable("testCacheTable") + } + + test("'CACHE TABLE tableName AS SELECT ..'") { + TestSQLContext.sql("CACHE TABLE testCacheTable AS SELECT * FROM testData") + assert(TestSQLContext.isCached("testCacheTable"), "Table 'testCacheTable' should be cached") + TestSQLContext.uncacheTable("testCacheTable") + } } diff --git a/sql/core/src/test/scala/org/apache/spark/sql/columnar/ColumnStatsSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/columnar/ColumnStatsSuite.scala index cde91ceb68c98..0cdbb3167ce36 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/columnar/ColumnStatsSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/columnar/ColumnStatsSuite.scala @@ -35,7 +35,7 @@ class ColumnStatsSuite extends FunSuite { def testColumnStats[T <: NativeType, U <: ColumnStats]( columnStatsClass: Class[U], columnType: NativeColumnType[T], - initialStatistics: Row) { + initialStatistics: Row): Unit = { val columnStatsName = columnStatsClass.getSimpleName diff --git a/sql/core/src/test/scala/org/apache/spark/sql/columnar/ColumnTypeSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/columnar/ColumnTypeSuite.scala index 75f653f3280bd..4fb1ecf1d532b 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/columnar/ColumnTypeSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/columnar/ColumnTypeSuite.scala @@ -23,6 +23,7 @@ import java.sql.Timestamp import org.scalatest.FunSuite import org.apache.spark.Logging +import org.apache.spark.sql.catalyst.expressions.GenericMutableRow import org.apache.spark.sql.catalyst.types._ import org.apache.spark.sql.columnar.ColumnarTestUtils._ import org.apache.spark.sql.execution.SparkSqlSerializer @@ -46,10 +47,12 @@ class ColumnTypeSuite extends FunSuite with Logging { def checkActualSize[T <: DataType, JvmType]( columnType: ColumnType[T, JvmType], value: JvmType, - expected: Int) { + expected: Int): Unit = { assertResult(expected, s"Wrong actualSize for $columnType") { - columnType.actualSize(value) + val row = new GenericMutableRow(1) + columnType.setField(row, 0, value) + columnType.actualSize(row, 0) } } @@ -147,7 +150,7 @@ class ColumnTypeSuite extends FunSuite with Logging { def testNativeColumnType[T <: NativeType]( columnType: NativeColumnType[T], putter: (ByteBuffer, T#JvmType) => Unit, - getter: (ByteBuffer) => T#JvmType) { + getter: (ByteBuffer) => T#JvmType): Unit = { testColumnType[T, T#JvmType](columnType, putter, getter) } @@ -155,7 +158,7 @@ class ColumnTypeSuite extends FunSuite with Logging { def testColumnType[T <: DataType, JvmType]( columnType: ColumnType[T, JvmType], putter: (ByteBuffer, JvmType) => Unit, - getter: (ByteBuffer) => JvmType) { + getter: (ByteBuffer) => JvmType): Unit = { val buffer = ByteBuffer.allocate(DEFAULT_BUFFER_SIZE) val seq = (0 until 4).map(_ => makeRandomValue(columnType)) diff --git a/sql/core/src/test/scala/org/apache/spark/sql/columnar/InMemoryColumnarQuerySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/columnar/InMemoryColumnarQuerySuite.scala index 0e3c67f5eed29..c1278248ef655 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/columnar/InMemoryColumnarQuerySuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/columnar/InMemoryColumnarQuerySuite.scala @@ -19,7 +19,7 @@ package org.apache.spark.sql.columnar import org.apache.spark.sql.catalyst.expressions.Row import org.apache.spark.sql.test.TestSQLContext -import org.apache.spark.sql.{SQLConf, QueryTest, TestData} +import org.apache.spark.sql.{QueryTest, TestData} class InMemoryColumnarQuerySuite extends QueryTest { import org.apache.spark.sql.TestData._ diff --git a/sql/core/src/test/scala/org/apache/spark/sql/columnar/NullableColumnAccessorSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/columnar/NullableColumnAccessorSuite.scala index 3baa6f8ec0c83..6c9a9ab6c3418 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/columnar/NullableColumnAccessorSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/columnar/NullableColumnAccessorSuite.scala @@ -45,7 +45,9 @@ class NullableColumnAccessorSuite extends FunSuite { testNullableColumnAccessor(_) } - def testNullableColumnAccessor[T <: DataType, JvmType](columnType: ColumnType[T, JvmType]) { + def testNullableColumnAccessor[T <: DataType, JvmType]( + columnType: ColumnType[T, JvmType]): Unit = { + val typeName = columnType.getClass.getSimpleName.stripSuffix("$") val nullRow = makeNullRow(1) diff --git a/sql/core/src/test/scala/org/apache/spark/sql/columnar/NullableColumnBuilderSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/columnar/NullableColumnBuilderSuite.scala index a77262534a352..f54a21eb4fbb1 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/columnar/NullableColumnBuilderSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/columnar/NullableColumnBuilderSuite.scala @@ -41,7 +41,9 @@ class NullableColumnBuilderSuite extends FunSuite { testNullableColumnBuilder(_) } - def testNullableColumnBuilder[T <: DataType, JvmType](columnType: ColumnType[T, JvmType]) { + def testNullableColumnBuilder[T <: DataType, JvmType]( + columnType: ColumnType[T, JvmType]): Unit = { + val typeName = columnType.getClass.getSimpleName.stripSuffix("$") test(s"$typeName column builder: empty column") { diff --git a/sql/core/src/test/scala/org/apache/spark/sql/columnar/PartitionBatchPruningSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/columnar/PartitionBatchPruningSuite.scala index 5d2fd4959197c..69e0adbd3ee0d 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/columnar/PartitionBatchPruningSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/columnar/PartitionBatchPruningSuite.scala @@ -28,7 +28,7 @@ class PartitionBatchPruningSuite extends FunSuite with BeforeAndAfterAll with Be val originalColumnBatchSize = columnBatchSize val originalInMemoryPartitionPruning = inMemoryPartitionPruning - override protected def beforeAll() { + override protected def beforeAll(): Unit = { // Make a table with 5 partitions, 2 batches per partition, 10 elements per batch setConf(SQLConf.COLUMN_BATCH_SIZE, "10") val rawData = sparkContext.makeRDD(1 to 100, 5).map(IntegerData) @@ -38,7 +38,7 @@ class PartitionBatchPruningSuite extends FunSuite with BeforeAndAfterAll with Be setConf(SQLConf.IN_MEMORY_PARTITION_PRUNING, "true") } - override protected def afterAll() { + override protected def afterAll(): Unit = { setConf(SQLConf.COLUMN_BATCH_SIZE, originalColumnBatchSize.toString) setConf(SQLConf.IN_MEMORY_PARTITION_PRUNING, originalInMemoryPartitionPruning.toString) } @@ -76,7 +76,7 @@ class PartitionBatchPruningSuite extends FunSuite with BeforeAndAfterAll with Be filter: String, expectedQueryResult: Seq[Int], expectedReadPartitions: Int, - expectedReadBatches: Int) { + expectedReadBatches: Int): Unit = { test(filter) { val query = sql(s"SELECT * FROM intData WHERE $filter") diff --git a/sql/core/src/test/scala/org/apache/spark/sql/columnar/compression/BooleanBitSetSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/columnar/compression/BooleanBitSetSuite.scala index e01cc8b4d20f2..d9e488e0ffd16 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/columnar/compression/BooleanBitSetSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/columnar/compression/BooleanBitSetSuite.scala @@ -20,6 +20,7 @@ package org.apache.spark.sql.columnar.compression import org.scalatest.FunSuite import org.apache.spark.sql.Row +import org.apache.spark.sql.catalyst.expressions.GenericMutableRow import org.apache.spark.sql.columnar.{NoopColumnStats, BOOLEAN} import org.apache.spark.sql.columnar.ColumnarTestUtils._ @@ -72,10 +73,14 @@ class BooleanBitSetSuite extends FunSuite { buffer.rewind().position(headerSize + 4) val decoder = BooleanBitSet.decoder(buffer, BOOLEAN) + val mutableRow = new GenericMutableRow(1) if (values.nonEmpty) { values.foreach { assert(decoder.hasNext) - assertResult(_, "Wrong decoded value")(decoder.next()) + assertResult(_, "Wrong decoded value") { + decoder.next(mutableRow, 0) + mutableRow.getBoolean(0) + } } } assert(!decoder.hasNext) diff --git a/sql/core/src/test/scala/org/apache/spark/sql/columnar/compression/DictionaryEncodingSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/columnar/compression/DictionaryEncodingSuite.scala index d2969d906c943..1cdb909146d57 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/columnar/compression/DictionaryEncodingSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/columnar/compression/DictionaryEncodingSuite.scala @@ -21,6 +21,7 @@ import java.nio.ByteBuffer import org.scalatest.FunSuite +import org.apache.spark.sql.catalyst.expressions.GenericMutableRow import org.apache.spark.sql.catalyst.types.NativeType import org.apache.spark.sql.columnar._ import org.apache.spark.sql.columnar.ColumnarTestUtils._ @@ -67,7 +68,7 @@ class DictionaryEncodingSuite extends FunSuite { val buffer = builder.build() val headerSize = CompressionScheme.columnHeaderSize(buffer) // 4 extra bytes for dictionary size - val dictionarySize = 4 + values.map(columnType.actualSize).sum + val dictionarySize = 4 + rows.map(columnType.actualSize(_, 0)).sum // 2 bytes for each `Short` val compressedSize = 4 + dictionarySize + 2 * inputSeq.length // 4 extra bytes for compression scheme type ID @@ -97,11 +98,15 @@ class DictionaryEncodingSuite extends FunSuite { buffer.rewind().position(headerSize + 4) val decoder = DictionaryEncoding.decoder(buffer, columnType) + val mutableRow = new GenericMutableRow(1) if (inputSeq.nonEmpty) { inputSeq.foreach { i => assert(decoder.hasNext) - assertResult(values(i), "Wrong decoded value")(decoder.next()) + assertResult(values(i), "Wrong decoded value") { + decoder.next(mutableRow, 0) + columnType.getField(mutableRow, 0) + } } } diff --git a/sql/core/src/test/scala/org/apache/spark/sql/columnar/compression/IntegralDeltaSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/columnar/compression/IntegralDeltaSuite.scala index 322f447c24840..73f31c0233343 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/columnar/compression/IntegralDeltaSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/columnar/compression/IntegralDeltaSuite.scala @@ -31,7 +31,7 @@ class IntegralDeltaSuite extends FunSuite { def testIntegralDelta[I <: IntegralType]( columnStats: ColumnStats, columnType: NativeColumnType[I], - scheme: IntegralDelta[I]) { + scheme: CompressionScheme) { def skeleton(input: Seq[I#JvmType]) { // ------------- @@ -96,10 +96,15 @@ class IntegralDeltaSuite extends FunSuite { buffer.rewind().position(headerSize + 4) val decoder = scheme.decoder(buffer, columnType) + val mutableRow = new GenericMutableRow(1) + if (input.nonEmpty) { input.foreach{ assert(decoder.hasNext) - assertResult(_, "Wrong decoded value")(decoder.next()) + assertResult(_, "Wrong decoded value") { + decoder.next(mutableRow, 0) + columnType.getField(mutableRow, 0) + } } } assert(!decoder.hasNext) diff --git a/sql/core/src/test/scala/org/apache/spark/sql/columnar/compression/RunLengthEncodingSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/columnar/compression/RunLengthEncodingSuite.scala index 218c09ac26362..4ce2552112c92 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/columnar/compression/RunLengthEncodingSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/columnar/compression/RunLengthEncodingSuite.scala @@ -19,6 +19,7 @@ package org.apache.spark.sql.columnar.compression import org.scalatest.FunSuite +import org.apache.spark.sql.catalyst.expressions.GenericMutableRow import org.apache.spark.sql.catalyst.types.NativeType import org.apache.spark.sql.columnar._ import org.apache.spark.sql.columnar.ColumnarTestUtils._ @@ -57,7 +58,7 @@ class RunLengthEncodingSuite extends FunSuite { // Compression scheme ID + compressed contents val compressedSize = 4 + inputRuns.map { case (index, _) => // 4 extra bytes each run for run length - columnType.actualSize(values(index)) + 4 + columnType.actualSize(rows(index), 0) + 4 }.sum // 4 extra bytes for compression scheme type ID @@ -80,11 +81,15 @@ class RunLengthEncodingSuite extends FunSuite { buffer.rewind().position(headerSize + 4) val decoder = RunLengthEncoding.decoder(buffer, columnType) + val mutableRow = new GenericMutableRow(1) if (inputSeq.nonEmpty) { inputSeq.foreach { i => assert(decoder.hasNext) - assertResult(values(i), "Wrong decoded value")(decoder.next()) + assertResult(values(i), "Wrong decoded value") { + decoder.next(mutableRow, 0) + columnType.getField(mutableRow, 0) + } } } diff --git a/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetQuerySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetQuerySuite.scala index b0a06cd3ca090..08f7358446b29 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetQuerySuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetQuerySuite.scala @@ -58,8 +58,7 @@ case class AllDataTypes( doubleField: Double, shortField: Short, byteField: Byte, - booleanField: Boolean, - binaryField: Array[Byte]) + booleanField: Boolean) case class AllDataTypesWithNonPrimitiveType( stringField: String, @@ -70,13 +69,14 @@ case class AllDataTypesWithNonPrimitiveType( shortField: Short, byteField: Byte, booleanField: Boolean, - binaryField: Array[Byte], array: Seq[Int], arrayContainsNull: Seq[Option[Int]], map: Map[Int, Long], mapValueContainsNull: Map[Int, Option[Long]], data: Data) +case class BinaryData(binaryData: Array[Byte]) + class ParquetQuerySuite extends QueryTest with FunSuiteLike with BeforeAndAfterAll { TestData // Load test data tables. @@ -108,26 +108,26 @@ class ParquetQuerySuite extends QueryTest with FunSuiteLike with BeforeAndAfterA test("Read/Write All Types") { val tempDir = getTempFilePath("parquetTest").getCanonicalPath val range = (0 to 255) - TestSQLContext.sparkContext.parallelize(range) - .map(x => AllDataTypes(s"$x", x, x.toLong, x.toFloat, x.toDouble, x.toShort, x.toByte, x % 2 == 0, - (0 to x).map(_.toByte).toArray)) - .saveAsParquetFile(tempDir) - val result = parquetFile(tempDir).collect() - range.foreach { - i => - assert(result(i).getString(0) == s"$i", s"row $i String field did not match, got ${result(i).getString(0)}") - assert(result(i).getInt(1) === i) - assert(result(i).getLong(2) === i.toLong) - assert(result(i).getFloat(3) === i.toFloat) - assert(result(i).getDouble(4) === i.toDouble) - assert(result(i).getShort(5) === i.toShort) - assert(result(i).getByte(6) === i.toByte) - assert(result(i).getBoolean(7) === (i % 2 == 0)) - assert(result(i)(8) === (0 to i).map(_.toByte).toArray) - } + val data = sparkContext.parallelize(range) + .map(x => AllDataTypes(s"$x", x, x.toLong, x.toFloat, x.toDouble, x.toShort, x.toByte, x % 2 == 0)) + + data.saveAsParquetFile(tempDir) + + checkAnswer( + parquetFile(tempDir), + data.toSchemaRDD.collect().toSeq) } - test("Treat binary as string") { + test("read/write binary data") { + // Since equality for Array[Byte] is broken we test this separately. + val tempDir = getTempFilePath("parquetTest").getCanonicalPath + sparkContext.parallelize(BinaryData("test".getBytes("utf8")) :: Nil).saveAsParquetFile(tempDir) + parquetFile(tempDir) + .map(r => new String(r(0).asInstanceOf[Array[Byte]], "utf8")) + .collect().toSeq == Seq("test") + } + + ignore("Treat binary as string") { val oldIsParquetBinaryAsString = TestSQLContext.isParquetBinaryAsString // Create the test file. @@ -142,37 +142,16 @@ class ParquetQuerySuite extends QueryTest with FunSuiteLike with BeforeAndAfterA StructField("c2", BinaryType, false) :: Nil) val schemaRDD1 = applySchema(rowRDD, schema) schemaRDD1.saveAsParquetFile(path) - val resultWithBinary = parquetFile(path).collect - range.foreach { - i => - assert(resultWithBinary(i).getInt(0) === i) - assert(resultWithBinary(i)(1) === s"val_$i".getBytes) - } - - TestSQLContext.setConf(SQLConf.PARQUET_BINARY_AS_STRING, "true") - // This ParquetRelation always use Parquet types to derive output. - val parquetRelation = new ParquetRelation( - path.toString, - Some(TestSQLContext.sparkContext.hadoopConfiguration), - TestSQLContext) { - override val output = - ParquetTypesConverter.convertToAttributes( - ParquetTypesConverter.readMetaData(new Path(path), conf).getFileMetaData.getSchema, - TestSQLContext.isParquetBinaryAsString) - } - val schemaRDD = new SchemaRDD(TestSQLContext, parquetRelation) - val resultWithString = schemaRDD.collect - range.foreach { - i => - assert(resultWithString(i).getInt(0) === i) - assert(resultWithString(i)(1) === s"val_$i") - } + checkAnswer( + parquetFile(path).select('c1, 'c2.cast(StringType)), + schemaRDD1.select('c1, 'c2.cast(StringType)).collect().toSeq) - schemaRDD.registerTempTable("tmp") + setConf(SQLConf.PARQUET_BINARY_AS_STRING, "true") + parquetFile(path).printSchema() checkAnswer( - sql("SELECT c1, c2 FROM tmp WHERE c2 = 'val_5' OR c2 = 'val_7'"), - (5, "val_5") :: - (7, "val_7") :: Nil) + parquetFile(path), + schemaRDD1.select('c1, 'c2.cast(StringType)).collect().toSeq) + // Set it back. TestSQLContext.setConf(SQLConf.PARQUET_BINARY_AS_STRING, oldIsParquetBinaryAsString.toString) @@ -275,34 +254,19 @@ class ParquetQuerySuite extends QueryTest with FunSuiteLike with BeforeAndAfterA test("Read/Write All Types with non-primitive type") { val tempDir = getTempFilePath("parquetTest").getCanonicalPath val range = (0 to 255) - TestSQLContext.sparkContext.parallelize(range) + val data = sparkContext.parallelize(range) .map(x => AllDataTypesWithNonPrimitiveType( s"$x", x, x.toLong, x.toFloat, x.toDouble, x.toShort, x.toByte, x % 2 == 0, - (0 to x).map(_.toByte).toArray, (0 until x), (0 until x).map(Option(_).filter(_ % 3 == 0)), (0 until x).map(i => i -> i.toLong).toMap, (0 until x).map(i => i -> Option(i.toLong)).toMap + (x -> None), Data((0 until x), Nested(x, s"$x")))) - .saveAsParquetFile(tempDir) - val result = parquetFile(tempDir).collect() - range.foreach { - i => - assert(result(i).getString(0) == s"$i", s"row $i String field did not match, got ${result(i).getString(0)}") - assert(result(i).getInt(1) === i) - assert(result(i).getLong(2) === i.toLong) - assert(result(i).getFloat(3) === i.toFloat) - assert(result(i).getDouble(4) === i.toDouble) - assert(result(i).getShort(5) === i.toShort) - assert(result(i).getByte(6) === i.toByte) - assert(result(i).getBoolean(7) === (i % 2 == 0)) - assert(result(i)(8) === (0 to i).map(_.toByte).toArray) - assert(result(i)(9) === (0 until i)) - assert(result(i)(10) === (0 until i).map(i => if (i % 3 == 0) i else null)) - assert(result(i)(11) === (0 until i).map(i => i -> i.toLong).toMap) - assert(result(i)(12) === (0 until i).map(i => i -> i.toLong).toMap + (i -> null)) - assert(result(i)(13) === new GenericRow(Array[Any]((0 until i), new GenericRow(Array[Any](i, s"$i"))))) - } + data.saveAsParquetFile(tempDir) + + checkAnswer( + parquetFile(tempDir), + data.toSchemaRDD.collect().toSeq) } test("self-join parquet files") { @@ -399,23 +363,6 @@ class ParquetQuerySuite extends QueryTest with FunSuiteLike with BeforeAndAfterA } } - test("Saving case class RDD table to file and reading it back in") { - val file = getTempFilePath("parquet") - val path = file.toString - val rdd = TestSQLContext.sparkContext.parallelize((1 to 100)) - .map(i => TestRDDEntry(i, s"val_$i")) - rdd.saveAsParquetFile(path) - val readFile = parquetFile(path) - readFile.registerTempTable("tmpx") - val rdd_copy = sql("SELECT * FROM tmpx").collect() - val rdd_orig = rdd.collect() - for(i <- 0 to 99) { - assert(rdd_copy(i).apply(0) === rdd_orig(i).key, s"key error in line $i") - assert(rdd_copy(i).apply(1) === rdd_orig(i).value, s"value error in line $i") - } - Utils.deleteRecursively(file) - } - test("Read a parquet file instead of a directory") { val file = getTempFilePath("parquet") val path = file.toString @@ -448,32 +395,19 @@ class ParquetQuerySuite extends QueryTest with FunSuiteLike with BeforeAndAfterA sql("INSERT OVERWRITE INTO dest SELECT * FROM source").collect() val rdd_copy1 = sql("SELECT * FROM dest").collect() assert(rdd_copy1.size === 100) - assert(rdd_copy1(0).apply(0) === 1) - assert(rdd_copy1(0).apply(1) === "val_1") - // TODO: why does collecting break things? It seems InsertIntoParquet::execute() is - // executed twice otherwise?! + sql("INSERT INTO dest SELECT * FROM source") - val rdd_copy2 = sql("SELECT * FROM dest").collect() + val rdd_copy2 = sql("SELECT * FROM dest").collect().sortBy(_.getInt(0)) assert(rdd_copy2.size === 200) - assert(rdd_copy2(0).apply(0) === 1) - assert(rdd_copy2(0).apply(1) === "val_1") - assert(rdd_copy2(99).apply(0) === 100) - assert(rdd_copy2(99).apply(1) === "val_100") - assert(rdd_copy2(100).apply(0) === 1) - assert(rdd_copy2(100).apply(1) === "val_1") Utils.deleteRecursively(dirname) } test("Insert (appending) to same table via Scala API") { - // TODO: why does collecting break things? It seems InsertIntoParquet::execute() is - // executed twice otherwise?! sql("INSERT INTO testsource SELECT * FROM testsource") val double_rdd = sql("SELECT * FROM testsource").collect() assert(double_rdd != null) assert(double_rdd.size === 30) - for(i <- (0 to 14)) { - assert(double_rdd(i) === double_rdd(i+15), s"error: lines $i and ${i+15} to not match") - } + // let's restore the original test data Utils.deleteRecursively(ParquetTestData.testDir) ParquetTestData.writeFile() diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala index 21ecf17028dbc..86d2aad71607a 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala @@ -229,7 +229,13 @@ private[hive] object HiveQl { SetCommand(Some(key), Some(value)) } } else if (sql.trim.toLowerCase.startsWith("cache table")) { - CacheCommand(sql.trim.drop(12).trim, true) + sql.trim.drop(12).trim.split(" ").toSeq match { + case Seq(tableName) => + CacheCommand(tableName, true) + case Seq(tableName,as, select@_*) => + CacheTableAsSelectCommand(tableName, + createPlan(sql.trim.drop(12 + tableName.length() + as.length() + 2))) + } } else if (sql.trim.toLowerCase.startsWith("uncache table")) { CacheCommand(sql.trim.drop(14).trim, false) } else if (sql.trim.toLowerCase.startsWith("add jar")) { @@ -243,15 +249,7 @@ private[hive] object HiveQl { } else if (sql.trim.startsWith("!")) { ShellCommand(sql.drop(1)) } else { - val tree = getAst(sql) - if (nativeCommands contains tree.getText) { - NativeCommand(sql) - } else { - nodeToPlan(tree) match { - case NativePlaceholder => NativeCommand(sql) - case other => other - } - } + createPlan(sql) } } catch { case e: Exception => throw new ParseException(sql, e) @@ -262,6 +260,19 @@ private[hive] object HiveQl { """.stripMargin) } } + + /** Creates LogicalPlan for a given HiveQL string. */ + def createPlan(sql: String) = { + val tree = getAst(sql) + if (nativeCommands contains tree.getText) { + NativeCommand(sql) + } else { + nodeToPlan(tree) match { + case NativePlaceholder => NativeCommand(sql) + case other => other + } + } + } def parseDdl(ddl: String): Seq[Attribute] = { val tree = diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/TableReader.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/TableReader.scala index 329f80cad471e..84fafcde63d05 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/TableReader.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/TableReader.scala @@ -25,16 +25,14 @@ import org.apache.hadoop.hive.ql.metadata.{Partition => HivePartition, Table => import org.apache.hadoop.hive.ql.plan.{PlanUtils, TableDesc} import org.apache.hadoop.hive.serde2.Deserializer import org.apache.hadoop.hive.serde2.objectinspector.StructObjectInspector - +import org.apache.hadoop.hive.serde2.objectinspector.primitive._ import org.apache.hadoop.io.Writable import org.apache.hadoop.mapred.{FileInputFormat, InputFormat, JobConf} import org.apache.spark.SerializableWritable import org.apache.spark.broadcast.Broadcast import org.apache.spark.rdd.{EmptyRDD, HadoopRDD, RDD, UnionRDD} - -import org.apache.spark.sql.catalyst.expressions.{Attribute, Row, GenericMutableRow, Literal, Cast} -import org.apache.spark.sql.catalyst.types.DataType +import org.apache.spark.sql.catalyst.expressions._ /** * A trait for subclasses that handle table scans. @@ -108,12 +106,12 @@ class HadoopTableReader( val hadoopRDD = createHadoopRdd(tableDesc, inputPathStr, ifc) val attrsWithIndex = attributes.zipWithIndex - val mutableRow = new GenericMutableRow(attrsWithIndex.length) + val mutableRow = new SpecificMutableRow(attributes.map(_.dataType)) + val deserializedHadoopRDD = hadoopRDD.mapPartitions { iter => val hconf = broadcastedHiveConf.value.value val deserializer = deserializerClass.newInstance() deserializer.initialize(hconf, tableDesc.getProperties) - HadoopTableReader.fillObject(iter, deserializer, attrsWithIndex, mutableRow) } @@ -164,33 +162,32 @@ class HadoopTableReader( val tableDesc = relation.tableDesc val broadcastedHiveConf = _broadcastedHiveConf val localDeserializer = partDeserializer - val mutableRow = new GenericMutableRow(attributes.length) - - // split the attributes (output schema) into 2 categories: - // (partition keys, ordinal), (normal attributes, ordinal), the ordinal mean the - // index of the attribute in the output Row. - val (partitionKeys, attrs) = attributes.zipWithIndex.partition(attr => { - relation.partitionKeys.indexOf(attr._1) >= 0 - }) - - def fillPartitionKeys(parts: Array[String], row: GenericMutableRow) = { - partitionKeys.foreach { case (attr, ordinal) => - // get partition key ordinal for a given attribute - val partOridinal = relation.partitionKeys.indexOf(attr) - row(ordinal) = Cast(Literal(parts(partOridinal)), attr.dataType).eval(null) + val mutableRow = new SpecificMutableRow(attributes.map(_.dataType)) + + // Splits all attributes into two groups, partition key attributes and those that are not. + // Attached indices indicate the position of each attribute in the output schema. + val (partitionKeyAttrs, nonPartitionKeyAttrs) = + attributes.zipWithIndex.partition { case (attr, _) => + relation.partitionKeys.contains(attr) + } + + def fillPartitionKeys(rawPartValues: Array[String], row: MutableRow) = { + partitionKeyAttrs.foreach { case (attr, ordinal) => + val partOrdinal = relation.partitionKeys.indexOf(attr) + row(ordinal) = Cast(Literal(rawPartValues(partOrdinal)), attr.dataType).eval(null) } } - // fill the partition key for the given MutableRow Object + + // Fill all partition keys to the given MutableRow object fillPartitionKeys(partValues, mutableRow) - val hivePartitionRDD = createHadoopRdd(tableDesc, inputPathStr, ifc) - hivePartitionRDD.mapPartitions { iter => + createHadoopRdd(tableDesc, inputPathStr, ifc).mapPartitions { iter => val hconf = broadcastedHiveConf.value.value val deserializer = localDeserializer.newInstance() deserializer.initialize(hconf, partProps) - // fill the non partition key attributes - HadoopTableReader.fillObject(iter, deserializer, attrs, mutableRow) + // fill the non partition key attributes + HadoopTableReader.fillObject(iter, deserializer, nonPartitionKeyAttrs, mutableRow) } }.toSeq @@ -257,38 +254,64 @@ private[hive] object HadoopTableReader extends HiveInspectors { } /** - * Transform the raw data(Writable object) into the Row object for an iterable input - * @param iter Iterable input which represented as Writable object - * @param deserializer Deserializer associated with the input writable object - * @param attrs Represents the row attribute names and its zero-based position in the MutableRow - * @param row reusable MutableRow object - * - * @return Iterable Row object that transformed from the given iterable input. + * Transform all given raw `Writable`s into `Row`s. + * + * @param iterator Iterator of all `Writable`s to be transformed + * @param deserializer The `Deserializer` associated with the input `Writable` + * @param nonPartitionKeyAttrs Attributes that should be filled together with their corresponding + * positions in the output schema + * @param mutableRow A reusable `MutableRow` that should be filled + * @return An `Iterator[Row]` transformed from `iterator` */ def fillObject( - iter: Iterator[Writable], + iterator: Iterator[Writable], deserializer: Deserializer, - attrs: Seq[(Attribute, Int)], - row: GenericMutableRow): Iterator[Row] = { + nonPartitionKeyAttrs: Seq[(Attribute, Int)], + mutableRow: MutableRow): Iterator[Row] = { + val soi = deserializer.getObjectInspector().asInstanceOf[StructObjectInspector] - // get the field references according to the attributes(output of the reader) required - val fieldRefs = attrs.map { case (attr, idx) => (soi.getStructFieldRef(attr.name), idx) } + val (fieldRefs, fieldOrdinals) = nonPartitionKeyAttrs.map { case (attr, ordinal) => + soi.getStructFieldRef(attr.name) -> ordinal + }.unzip + + // Builds specific unwrappers ahead of time according to object inspector types to avoid pattern + // matching and branching costs per row. + val unwrappers: Seq[(Any, MutableRow, Int) => Unit] = fieldRefs.map { + _.getFieldObjectInspector match { + case oi: BooleanObjectInspector => + (value: Any, row: MutableRow, ordinal: Int) => row.setBoolean(ordinal, oi.get(value)) + case oi: ByteObjectInspector => + (value: Any, row: MutableRow, ordinal: Int) => row.setByte(ordinal, oi.get(value)) + case oi: ShortObjectInspector => + (value: Any, row: MutableRow, ordinal: Int) => row.setShort(ordinal, oi.get(value)) + case oi: IntObjectInspector => + (value: Any, row: MutableRow, ordinal: Int) => row.setInt(ordinal, oi.get(value)) + case oi: LongObjectInspector => + (value: Any, row: MutableRow, ordinal: Int) => row.setLong(ordinal, oi.get(value)) + case oi: FloatObjectInspector => + (value: Any, row: MutableRow, ordinal: Int) => row.setFloat(ordinal, oi.get(value)) + case oi: DoubleObjectInspector => + (value: Any, row: MutableRow, ordinal: Int) => row.setDouble(ordinal, oi.get(value)) + case oi => + (value: Any, row: MutableRow, ordinal: Int) => row(ordinal) = unwrapData(value, oi) + } + } // Map each tuple to a row object - iter.map { value => + iterator.map { value => val raw = deserializer.deserialize(value) - var idx = 0; - while (idx < fieldRefs.length) { - val fieldRef = fieldRefs(idx)._1 - val fieldIdx = fieldRefs(idx)._2 - val fieldValue = soi.getStructFieldData(raw, fieldRef) - - row(fieldIdx) = unwrapData(fieldValue, fieldRef.getFieldObjectInspector()) - - idx += 1 + var i = 0 + while (i < fieldRefs.length) { + val fieldValue = soi.getStructFieldData(raw, fieldRefs(i)) + if (fieldValue == null) { + mutableRow.setNullAt(fieldOrdinals(i)) + } else { + unwrappers(i)(fieldValue, mutableRow, fieldOrdinals(i)) + } + i += 1 } - row: Row + mutableRow: Row } } } diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/TestHive.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/TestHive.scala index a3bfd3a8f1fd2..70fb15259e7d7 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/TestHive.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/TestHive.scala @@ -35,12 +35,13 @@ import org.apache.spark.sql.catalyst.analysis._ import org.apache.spark.sql.catalyst.plans.logical.{CacheCommand, LogicalPlan, NativeCommand} import org.apache.spark.sql.catalyst.util._ import org.apache.spark.sql.hive._ +import org.apache.spark.sql.SQLConf /* Implicit conversions */ import scala.collection.JavaConversions._ object TestHive - extends TestHiveContext(new SparkContext("local", "TestSQLContext", new SparkConf())) + extends TestHiveContext(new SparkContext("local[2]", "TestSQLContext", new SparkConf())) /** * A locally running test instance of Spark's Hive execution engine. @@ -90,6 +91,10 @@ class TestHiveContext(sc: SparkContext) extends HiveContext(sc) { override def executePlan(plan: LogicalPlan): this.QueryExecution = new this.QueryExecution { val logical = plan } + /** Fewer partitions to speed up testing. */ + override private[spark] def numShufflePartitions: Int = + getConf(SQLConf.SHUFFLE_PARTITIONS, "5").toInt + /** * Returns the value of specified environmental variable as a [[java.io.File]] after checking * to ensure it exists diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveComparisonTest.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveComparisonTest.scala index 671c3b162f875..79cc7a3fcc7d6 100644 --- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveComparisonTest.scala +++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveComparisonTest.scala @@ -250,9 +250,9 @@ abstract class HiveComparisonTest } try { - // MINOR HACK: You must run a query before calling reset the first time. - TestHive.sql("SHOW TABLES") - if (reset) { TestHive.reset() } + if (reset) { + TestHive.reset() + } val hiveCacheFiles = queryList.zipWithIndex.map { case (queryString, i) => diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala index 6bf8d18a5c32c..8c8a8b124ac69 100644 --- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala +++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala @@ -295,8 +295,16 @@ class HiveQuerySuite extends HiveComparisonTest { "SELECT (CASE WHEN key > 2 THEN 3 WHEN 2 > key THEN 2 ELSE 0 END) FROM src WHERE key < 15") test("implement identity function using case statement") { - val actual = sql("SELECT (CASE key WHEN key THEN key END) FROM src").collect().toSet - val expected = sql("SELECT key FROM src").collect().toSet + val actual = sql("SELECT (CASE key WHEN key THEN key END) FROM src") + .map { case Row(i: Int) => i } + .collect() + .toSet + + val expected = sql("SELECT key FROM src") + .map { case Row(i: Int) => i } + .collect() + .toSet + assert(actual === expected) } @@ -559,9 +567,9 @@ class HiveQuerySuite extends HiveComparisonTest { val testVal = "test.val.0" val nonexistentKey = "nonexistent" val KV = "([^=]+)=([^=]*)".r - def collectResults(rdd: SchemaRDD): Set[(String, String)] = - rdd.collect().map { - case Row(key: String, value: String) => key -> value + def collectResults(rdd: SchemaRDD): Set[(String, String)] = + rdd.collect().map { + case Row(key: String, value: String) => key -> value case Row(KV(key, value)) => key -> value }.toSet clear()